On the other hand, misorientation angles have weak influence on the resistance across MoS2 GBs, ranging from about 130 Ω μm for low mismatch angles to about 6000 Ω μm for 21°. The interface resistance across graphene-MoS2 heterojunctions also exhibits a strong dependence on misorientation angles with resistance values ranging from about 100 Ω μm for low-mismatch angles in Class-I (symmetric) interfaces to 1015 Ω μm for 14° mismatch in Class-II (asymmetric) interfaces. Overall, symmetric homo/heterojunctions exhibit a weak dependence on misorientation angles, while in MoS2 both symmetric and asymmetric GBs show a gradual dependence on mismatch angles.We study the impact of grain boundaries (GB) and misorientation angles between grains on electronic transport in 2-dimensional materials. Here we have developed a numerical model based on the first-principles electronic bandstructure calculations in conjunction with a method which computes electron transmission coefficients from simultaneous conservation of energy and momentum at the interface to essentially evaluate GB/interface resistance in a Landauer formalism. We find that the resistance across graphene GBs vary over a wide range depending on misorientation angles and type of GBs, starting from 53 Ω  Besides graphene, transition metal dichalcogenides (TMDs) are another class of two-dimensional (2D) materials which have attracted intense research interests in recent years. The potential applications of graphene and TMDs have motivated mass scale production of large-area films. Among the most popular methods, chemical-vapor deposition (CVD) on transition metal substrates is relatively cheap and extensively used to grow high quality large two-dimensional sheets1. However, CVD-grown films are typically found to be polycrystalline in nature, consisting of many single crystalline grains each with random crystal orientation and separated by grain boundaries (GBs)2. Several studies have reported that grain boundaries in 2D materials impact both their electronic7 and thermal properties10.Graphene, a monolayer of spμm11 to tens of kΩ μm4. Huang et al.12 showed a wide distribution of misorientation angles between adjacent grains in a polycrystalline monolayer graphene sheet with a preferential low angle growth of about 7°. The GB resistance across such GBs was found to be about 240 Ω μm. Contrasting this to the sheet resistance of 700 et al.13 observed a reduction in mobility in CVD-grown graphene and attributed it to the strong carrier scattering at grain boundaries. Clark et al.14 found resistance across graphene GBs to be varying between 40–140 Ω μm for samples with misorientation angles ranging from 9° to 21°. The resistivity of GBs was more than 3 times the bulk resistivity of the grains consistently across all of their samples. There was a positive correlation between misorientation angles and GB resistance, but the width of the transition region surrounding the GB also played a role.The earliest of these studies focused on the electrical resistance across graphene GBs. Experimentally, graphene GB resistance has been found to vary over a broad range from a few Ω 19 which have helped to gain more insight on transport across graphene GBs. Yazyev and Louie15 found that GBs across grains represented by the same translational vectors are highly transparent to charge carriers with a transmission of about 80%, whereas GBs formed by grains with different translational vectors behave as perfect reflectors of carriers. Vancso et al.16 performed wave packet dynamical transport calculations to show that transmission properties across graphene GBs depend on misorientation angles as well as localized structures at the boundaries. Zhang et al.17 showed that intrinsic (defect-free) GBs are almost transparent to carrier transport in highly symmetric GBs. They concluded that the degradation in transmission mainly comes from the extrinsic defects at the boundaries which results in the passivation of the π-orbital. Recently, Sun et al.18 investigated electrical properties along different transport directions with respect to the GB direction using Density Functional Theory (DFT) calculations combined with Green’s function technique. They showed that the zero band gap nature of graphene bandstructure remains intact even in the presence of GBs. They also found that there is an at least 50% current suppression in the transport across GBs as compared to the current in pristine graphene. Despite the numerous studies on various types of graphene GBs, the dependence of GB resistance on misorientation angles is still inconclusive.Besides experimental measurements, there are several theoretical studies225; however, little is known about the impact of misorientation angles on its GB resistance. Najmaei et al.20 studied the individual and collective effect of GBs on electronic transport properties and found that the carrier mobility shows a weak dependence on channel length up to 75 μm. Kang et al.21 also reported a similar dependence of field-effect mobility on channel length, again indicating that GBs don’t significantly degrade the electronic transport properties in CVD-grown MoS2. This observation was further corroborated by Schmidt et al.22, where they demonstrate that the electronic properties of CVD-grown monolayer MoS2 are comparable to those of their exfoliated counterparts. In contrast, Ly et al.25 showed that MoS2 sheets exhibit very poor electrical transport properties (mobilities below 70 cm2 V−1 s−1) for all their devices with different misorientation angles. They observed a positive but non-linear correlation between field-effect mobility and misorientation angles.There has also been a growing interest in electrical transport of CVD-grown MoS29 as well as vertical32 2D heterostructures has recently gained significant research attention with particular focus on graphene-contacted MoS2 lateral (in-plane) heterostructures36. Graphene has been reported to form an ohmic contact with MoS237, resulting in an increase in mobility up to an order of magnitude as compared to that of in metal-MoS2 field-effect transistors (FETs). This calls for investigating the role of misorientation angles in determining the graphene-MoS2 interface resistance in such heterostructures. Throughout the numerous studies of the resistance of GBs and interfaces, a common thread is that the resistance spans a wide range of values depending on mismatch angle. A definitive trend explaining this variation, especially in MoS2 GBs and graphene-MoS2 interfaces, still requires further investigation.Electronic transport in lateral2 grain boundaries, as well as graphene-MoS2 heterojunctions. We use the transmission coefficients to compute the conductance of the boundaries/interfaces as a function of both mismatch angle and carrier concentration. In Sec. 2 we further detail our approach and delineate two different classes of GBs (twin and tilt homojunctions) and interfaces (Class-I and II heterojunctions). In Sec. 3, we discuss our results showing that transport across twin homojunctions and Class-I heterojunctions show a weak dependence on mismatch angles, whereas the resistance across tilt homojunctions and Class-II heterojunctions exhibits a strong dependence on mismatch angles. We conclude in Sec. 4 that GBs play a moderate role in MoS2 due to its parabolic bands, but can be quite significant in graphene and large-mismatch graphene-MoS2 heterostructures owing to graphene’s steep linear Dirac cones.In this paper, we focus on the fundamentals behind the impact of grain misorientation angles in 2D homojunctions and heterojunctions. Starting from electronic structure obtained through first principles Density Functional Theory (DFT), we calculate the transmission coefficients and boundary/interface resistances for graphene and MoS15 to calculate the transmission coefficient of electrons across a graphene grain boundary. The interface resistance is calculated in the following steps: bandstructure calculations for graphene and MoS2 individually from the first principles, rotation of the Brillouin zones (BZ) to account for the misorientation angle between adjacent grains, calculation of electron transmission across the interface from the energy and momentum conservation, and finally computing the interface resistance in the Landauer formalism. For heterojunctions between dissimilar materials, an additional second step involves band alignment at the interface based on the Schottky-Mott rule.To study the impact of misorientation angles on interface resistance, we have developed a numerical model based on first-principles DFT electronic bandstructure calculations and electron transmission coefficients from simultaneous energy and momentum conservation. The latter is an extension of the approach originally proposed by Yazyev and Louie2 individually from first principles using Density Functional Theory (DFT) as implemented within the open-source distribution Quantum Espresso38 . It is followed by the alignment of the bands at the interface. In homojunctions such as graphene-graphene GBs and MoS2-MoS2 GBs, the bands are always well-aligned at the interface, whereas in heterojunctions, such as the graphene-MoS2 GBs, the bands need to be aligned. In contrast to the planar charge in a 3D interface, a 2D heterojunction forms a line dipole at the junction39. It has been shown that in 2D heterojunctions, the effect of this interfacial dipole vanishes when the overall dimensions of the device are much larger than the characteristic junction-width, typically about 10 nm39. As a result, the band alignment in 2D heterojunctions is far less sensitive to the interfacial details and the band alignment closely follows the Schottky-Mott rule39.First, we calculate the electronic bandstructure for single-layer graphene and MoS2 are treated as semi-infinte, so we use the Schottky-Mott rule40 and align the vacuum levels of the two materials at the interface. Next, the work function of graphene (ϕgraphene = 4.55 eV41) and the electron affinity of MoS2 (42) are used to align the respective bands away from the interface relative to the vacuum level. Due to the difference in the work function of graphene and electron affinity of MoS2, an energy barrier 2 side near the interface to account for the energy barrier height in equilibrium. The amount of band-bending on MoS2 side, which is also a function of carrier concentration nC, is given by 26. The carrier concentration typically depends on the level of impurities, doping, or gating45.In our case, the graphene and MoSL and ΘR, each being the angle of rotation between the grain on the left and the right side with respect to the interface, taken here as reference, as shown in Fig. L is taken to be positive for anticlockwise rotation of the left grain, whereas ΘR is positive for clockwise rotation of the right grain. We define misorientation angle as ΘM = ΘL + ΘR. To include the effect of the misorientation angle in our calculation, the wavevectors in the first Brillouin zone are rotated by ΘL for the left grain and ΘR for the grain on the right hand side of the interface. The rotation of the Brillouin zone does not affect the aforementioned band structure alignment at the interface.The orientation of the grains with respect to the GB/interface is defined by two angles ΘL = ΘR = ΘM/2) and the second is when only one of the grains is rotated away from the interface . In literature, the former type of symmetric grain boundaries are referred to as twin GBs and the latter as the most asymmetric tilt GBs.In 2D materials, GBs can be of different types depending on both the orientation of each grain with respect to the grain boundary and the orientation of the grains with respect to each other. One extreme is when both the grains are rotated symmetrically by equal angles away from the GB in opposite directions  GBs depending on the position of the boundary itself. For example, given that ΘM is 4° we can have ΘL = ΘR = ΘM/2 (twin GBs), or ΘL = 0° and ΘR = ΘM (the most asymmetric tilt GB), or intermediate cases such as ΘL = 1° and ΘR = 3°, and so on so forth. In order to denote these intermediate tilt cases, we introduce an angle ΘB, which is defined as the angle, in the anticlockwise direction, that the boundary makes with the reference line. So, an intermediate case of ΘL = 1° and ΘR = 3° can be represented as ΘM = 4° and ΘB = 1°.So far, we have discussed the two extreme cases of GBs for a given misorientation angle Θ46. From translational symmetry, transmission requires simultaneous conservation of energy and transverse momentum of the incident electron across the interface. Momentum conservation requires that the parallel component of the incident wave vector b using the perpendicular components of the incident b(E) by averaging the mode-dependent transmission coefficient τb(k) over the constant energy contour, described by δ(E − Eb(k)), using the 2D version of the linear extrapolation approach described by Gilat and Raubenheimer47 asbDb(E), shown in Fig. E) asf/∂E over energyC is the bottom of the conduction band and Emax is the highest electron energy in the first four conduction bands and f(E) is the Fermi-Dirac distribution function f(E) = [1 + exp((E − EF)/kBT)]−1.The effect of GB/interface on transport is incorporated by using boundary conditions based on quantum-mechanical wave continuityentclass1pt{minimaRGB respectively for various misorientation angles in twin GBs. We see in Fig. E) equals 1, is obtained for 0° mismatch angle at any given energy level. However, as the misorientation angle increases, the modes that do not conserve energy and transverse momentum are reflected at the interface, resulting in a reduction of the transmission coefficient, which varies between 0.8 and 0.5 for various mismatch angles. Besides band gap, the energy range for which there is no transmission (Γ(E) = 0) is referred here as transmission/transport gap. In twin GBs, we note that even for large mismatch angles there is no transmission gap in the energy spectrum.We calculate the transmission and resistance of graphene GBs in order to explore the impact of the misorientation angle. The angle dependence of GB resistance largely depends on the type (tilt or twin) of the GB. Figure E) = 1; in contrast, Yazyev and Louie15 reported a linear transmission probability T(E) with energy. They used a non-equilibrium Green’s function (NEGF) formalism to calculate conductance across graphene grain boundaries. In the coherent transport regime, the conductance from NEGF formalism reduces to the conductance in Landauer formalism48, given by49T(E) in the NEGF formailsm is analogous to our transport distribution function Ξ(E). For the graphene GBs with 0° mismatch, Ξ(E) in Eq. Db(E), which is linear with energy [as shown in Fig. T(E) vs. energy plot from NEGF15.For GBs with 0° mismatch angle, we obtain a coefficient Γ which is centered at EF also shifts towards higher energy levels. As the DOS in graphene is proportional to energy near the Dirac point (from Eq. E) also increases with energy away from the Dirac point. Thus the value of the integral in Eq. In Fig. from Eq. , the TDFFigure μm to several kΩ μm3. The wide variation in GB resistance can be fully explained with the trends observed in Fig. μm at 4° mismatch to several thousands of GΩ μm at 14° mismatch, even at high carrier concentration of about 1013 cm−2. The transmission coefficient eventually becomes zero for misorientation angles beyond 14° mismatch due to the large transmission gap in tilt GBs and we observe extremely high values of resistances. In contrast, the resistance of twin GBs in near-intrinsic graphene varies from 400 Ω μm at low to about 1 kΩ μm at high mismatch angles, while at high carrier concentration it varies over a very narrow range of about 90 Ω μm at 4° mismatch to 110 Ω μm at 14° mismatch. Our calculated graphene GB resistances include a ballistic resistance of 53 Ω μm at high carrier concentration of 1013 cm−2 and 424 Ω μm at intrinsic carrier concentration. After removing the ballistic resistance, the calculated GB resistance for a low-mismatch twin GBs of about 1° at high carrier concentration is 8 Ω μm. This is in good agreement with Grosse et al.11.Previously, it was found that the GB resistance across graphene GBs varies within a wide range from a few Ω 2 GBs, we use the same procedure as used for graphene GBs in the previous section. The transmission coefficient as a function of energy is plotted in Fig. 2. We also observe a gradual reduction in transmission coefficient with increasing misorientation angles as compared to that of graphene GBs. However, there is no transmission gap found for MoS2 twin GBs, similar to what we observed in graphene twin GBs. Corresponding to the transmission coefficient for various misorientation angles, the boundary resistance across MoS2 twin grain boundaries vs. carrier concentration is shown in Fig. RGB in MoS2 twin GBs are almost double than the values of GB resistance in graphene twin boundaries for a carrier concentration of 1 × 1012 cm−2, whereas for large carrier concentrations between 6 × 1012 and 9 × 1012 cm−2, MoS2 twin GBs have GB resistance similar to that of graphene twin GBs.To study electronic resistance across MoS2 tilt GBs. It can be seen in Fig. 2 twin GBs. Like in tilt graphene GBs, a transmission gap is also observed in tilt MoS2 GBs for large misorientation angles, however the transmission gap in MoS2 is much smaller than that of graphene. We attribute this trend to the flatter parabolic conduction band bottom of MoS2 as compared to the steep conical bandstructure of graphene around the Dirac point. The variation of GB resistance with misorientation angle is quite distinct in this case as compared to the variation of RGB in graphene tilt GBs. It is important to note that the resistance across MoS2 GBs is much smaller than what we found in graphene tilt GBs. Thus, misorientation of adjacent grains across grain boundaries can cause a significant reduction in electronic conductance in polycrystalline graphene, while GBs in polycrystalline MoS2 might not play such a strong role in electron conduction, which is in good agreement with few recent reports on electronic transport in CVD-grown MoS222.Figure M and ΘB for graphene and MoS2 GBs respectively. The calculated value of resistances across graphene GBs range from few tens of Ω μm to about 1013 Ω μm depending on the ΘM (the angle between the two grains) and ΘB (the position of the boundary with respect to the left grain). However, the GB resistance across MoS2 GBs vary over a relatively narrow range of about 130 Ω μm to 5700 Ω μm for various combinations of ΘM and ΘB. Thus, we can see that for a given misorientation angle, one can have different GB resistance depending on the position of the GB with respect to the grains, and any resistance value falling in this range can be explained by a combination ΘM and ΘB.Figure 2 to differentiate with those of homojunctions. When graphene (taken here to be on left side of the boundary) and MoS2 (right side of the boundary) grains are rotated by equal angles with respect to the interface i.e. ΘL = ΘR, we use the term Class-I interface, whereas when The interfaces formed between two dissimilar materials (heterojunctions) are different from those of homojunctions because of the difference in the properties of the grains on either side of the interface—including electron affinity, work function, and bandstructure. So, before discussing about electron transport across such heterojunctions, we redefine the nomenclature of the interfaces formed between graphene and MoS2 Class-I interface for various misorientation angles at a carrier concentration of 1 × 1012 cm−2. Due to the difference in the work function and electron affinity in graphene and MoS2, the bands bend and an energy barrier  is formed at the interface. Like in homojunctions, the band alignment at the interface is independent of the misorientation angle, and thus, the barrier height is also independent of ΘM. In Fig. 12 cm−2, the interface resistance is in the order of 108 Ω μm because of the large energy barrier. However, at high carrier concentrations between 6 × 1012 cm−2 and 9 × 1012 cm−2, the interface resistance reduces significantly because the energy barrier between graphene and MoS2 almost disappears at such concentrations and they behave like Ohmic contacts.Figure 2 interfaces at a carrier concentration of 1 × 1012 cm−2. The transmission coefficient decreases with increasing mismatch angle similar to the tilt GBs in graphene GBs. A transmission gap is formed in addition to the existing potential barrier, marked in the figure, and this transmission gap widens with increasing misorientation angles. Transmission becomes zero for large mismatch angles beyond 14°. This strong dependence of mismatch angle on transmission coefficient leads to a strong dependence of the interface resistance on misorientation angles in Class-II graphene-MoS2 heterojunctions, which can be seen in Fig. 12 cm−2, the interface resistance varies from about 108 for low mismatch angles to 1014 Ω μm for a mismatch of 14°, whereas at high concentrations the interface resistance ranges from about 102 for low mismatch angles to 108 Ω μm for a mismatch of 14°.Figure 2-MoS2 GBs, the band alignment is independent of the position of the Fermi level so the transmission coefficient is also independent of carrier concentration. In contrast, the barrier height in heterojunctions is a function of carrier concentration via the position of the Fermi level, owing to the difference in DOS between graphene and MoS2. The transmission coefficient in Class-I graphene-MoS2 interface is plotted with carrier concentration in Fig. 2 interface, that is 0° mismatch. The shape of the Γ(E) vs. energy does not change with carrier concentration rather the curves get shifted towards the left in energy due to the decrease in energy barrier height with carrier concentration. In Fig. In homojunctions like graphene-graphene and MoS2-MoS2, and Gr-MoS2 interfaces. It can be seen that, in general, symmetric twin GBs in homojunctions and Class-I interfaces in heterojunctions show a very weak dependence on the degree of mismatch between adjacent grains, whereas tilt GBs in homojunctions and Class-II interfaces in heterojunctions exhibit strong dependence on misorientation angles except in MoS2, where both tilt and twin GBs are found to show a weak dependence on mismatch angles. The weak angle dependence in MoS2-MoS2 GBs can be attributed to the flat parabolic conduction band because of which the underlap in the bandstructures on the either side of the GB is quite small even at large mismatch angles. In order to explain the wide range of the graphene GB resistances in the literature via misorientation angle and type of GBs, the data from the literature has also been included in the figure. The yellow markers in the figure denote the combinations of ΘM and ΘB obtained by fitting the experimental measurements by Kochat et al.50 (ΘB = 2.83° and 3° for ΘM = 12° and 22° respectively), Clark et al.14 , and Yu et al.3 (ΘB = 3.1° for ΘM = 28°).Figure 9 and the presence of localized electronic states, which have been observed at 3D interfaces51 and 2D grain boundaries53. The localized states are not included in our model, but could be treated by modifying Db(E) in Eq. 2 interfaces. Then localized states might introduce additional channels for transmission and lead to slightly higher GB conductance than what we report here without these localized states. In that sense, our conductance values could be thought of as a lower bound.The aim of our study is to understand the effect of misorientation angle on GB conductance. There could be additional effects due to grain boundary roughness2 interfaces varies over a very wide range depending on the degree of mismatch between adjacent grains and type of GBs. The transmission coefficient across symmetric interfaces (twin GBs in homojunctions and Class-I interfaces in heterojunctions) is found to be less sensitive to misorientation angles between adjacent grains because they deflect electrons rather coherently. In these symmetric interfaces, there is no transmission gap. On the other hand, the transmission across asymmetric interfaces (tilt GBs in homojunctions and Class-II interfaces in heterojunctions) is largely diminished by mismatch angles and a transmission gap opens up in the energy spectrum. In contrast to graphene-graphene tilt GBs, the resistance across MoS2-MoS2 tilt GBs show relatively much weaker dependence on mismatch angles. This is attributed to the flat parabolic conduction band bottom in MoS2 as compared to the steep conical conduction band bottom in graphene. As a result, the rotation of the BZ in MoS2 by large angles causes a small transmission gap, whereas even a small misorientation angle across graphene GBs gives rise to a large transmission gap. In homojunctions, the bands are identical on either side of the interface and the response to the carrier concentration, and hence the back-gated voltage, is also uniform on both sides. Thus, for a given misorientation angle, the variation of transmission coefficient vs. energy is independent of carrier concentration in homojunctions. In heterojunctions, the bands are aligned at the interface using the macroscopic variables, including work function and electron affinity, based on Schottky-Mott rule, forming an energy barrier at the interface. The band alignment, and with it the energy barrier between graphene and MoS2, reduces with the carrier concentration because of the differences in their densities-of-states. Consequently, the interface resistance strongly decreases with carrier concentration in heterojunctions in both classes of interfaces. In summary, electrical transport across twin homojunctions and Class-I heterojunctions shows a weak dependence on mismatch angles, whereas the resistance across tilt homojunctions and Class-II heterojunctions exhibits a strong dependence on mismatch angles.In conclusion, we find that misorientation angle between two adjacent grains plays a very significant role in both homojunctions and heterojunctions. We show that the resistance across graphene GBs and graphene-MoS54. For MoS2, we used a nonrelativistic NCPP for Mo and a scalar relativistic NCPP for S. Both potentials employed a Martins-Troullier method with a Perdew-Wang LDA exchange correlation55. The lattice constants are a = 2.459 Å for graphene and a = 3.125 Å, z = 3.11 Å for MoS2, where z is the distance between chalcogen atoms. To ensure that interplanar interactions are neglected, the repeating images of the monolayers are seperated by a 20 Å vacuum. The cutoff energy for plane waves was 120 Ry for graphene and 140 Ry for MoS2. We used a convergence threshold of 10−15 on a Monkhorst-Pack grid sizes of 8 × 8 × 1 for graphene and 6 × 6 × 4 for MoS2 for the initial total energy calculation and then performed a bandstructure calculation on a dense grid of 25,208 k-points (wavevectors) with a convergence threshold of 10−12. We used the central difference method to obtain the electron velocities per band which, in turn, are subsequently used in calculating the electronic density of states (DOS) and other transport properties including interfacial transmission and resistance of the interface.For graphene, we used a scalar relativistic, norm-conserving pseudopotential (NCPP) which implements a direct-fit Von Barth-Car method with a Perdew-Zunger local density approximation (LDA) exchange-correlation functionalM) is 0°. In the diffusive limit (Ohmic regime) when the dimension of the conductor is large compared to the carrier mean free path, the conductance varies inversely with length. One would expect the conductance to become infinite when the conductor length tends to zero. However, it has been experimentally found in both metals56 and semiconductors58 that the measured conductance converge to a finite value called ballistic conductance. The regime where we see this limiting behavior is called ballistic regime. In this regime, characterized by an absence of scattering, the conductor has no resistance–the ballistic resistance is not the resistance of the conductor but the contact resistance48.We derive an analytical expression for the ballistic resistance across graphene GBs and compare it with the numerically computed values of ballistic resistance at different carrier concentrations. We define ballistic resistance as the resistance between two perfectly-matched grains, that is when misorientation angle 〉 is calculated by 2D averaging of velocity of all the modes, vF is the Fermi velocity (≈106 ms−1), which is computed from the slope of the bandstructure (E-k relationship) around Dirac point. DD2(E) is the 2D density of states.The channel number at any energy (E) for a given width of the ribbon is calculated asgs and gv are constants related to the spin of electron and valley degeneracy respectively. For graphene gv = 2 and gs = 2 for electrons. f0(E) is the equilibrium Fermi-Dirac distribution function, Rball in graphene, which is the reciprocal of Gball,2D, is inversely proportional to the square root of carrier concentration. On using the values of the constants in Eq. 10 cm−2, the analytical value of Rball in graphene is about 405 Ω μm.The dispersion of graphene around the Dirac point is approximated by the relation mentclasspt{miniman0 = 8 × 1010 cm−2), the numerically calculated ballistic resistance is 424 Ω μm, which compares quite well with the analytical value of 405 Ω μm. In Fig. E) is 1 for the entire energy range, showing perfect transmission for 0° mismatch (perfectly-matched grains). The curve encompassing the blue area in the figure is the Fermi window function, which is defined as the derivative of Fermi-Dirac distribution function with respect to energy, for intrinsic carrier concentration that is when the Fermi level EF is around the Dirac point and the electron concentration is equal to the hole concentration. Eq. RGB when plotted against carrier concentration as shown in Fig. We compare these analytically calculated values of ballistic resistance for different carrier concentrations with our numerically calculated values as shown in Fig.  The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.


Zenon Pylyshyn argues that cognitively driven attentional effects do not amount to cognitive penetration of early vision because such effects occur either before or after early vision. Critics object that in fact such effects occur at all levels of perceptual processing. We argue that Pylyshyn’s claim is correct—but not for the reason he emphasizes. Even if his critics are correct that attentional effects are not external to early vision, these effects do not satisfy Pylyshyn’s requirements that the effects be direct and exhibit semantic coherence. In addition, we distinguish our defense from those found in recent work by Raftopoulos and by Firestone and Scholl, argue that attention should not be assimilated to expectation, and discuss alternative characterizations of cognitive penetrability, advocating a kind of pluralism. What we think can affect what we see. For example, if you want some chocolate and think it is to your left, you might turn to look that way. What you now see will differ from what you saw before: a half-eaten bar on the counter rather than the empty cupboard. In this case, a kind of attention plays a mediating role: what you think causes you to change the orientation of your gaze, which in turn has obvious effects on what you see.What does this show about the relation between cognition  and perception? Certainly, it shows that there are ways the former can causally affect the latter. Does it show something more significant? Might it require a reconception of cognitive architecture—perhaps even call into question the distinction between perception and conception? Might it deprive us of a theory-neutral basis for adjudicating among competing hypotheses, or undermine perception’s apparent role in providing independent warrant to beliefs?here, not there) but not alter that which it selects, it would seem only to constrain the basis for one’s beliefs, not to affect the epistemic relevance of what one does see.At least for the case at hand, this seems unlikely . Because cognitive effects on perception via bodily movement are both unsurprising and indirect, it is unclear how they might challenge or reshape the distinction between seeing and thinking. Because this sort of attention can be so readily redirected, it is not obvious how it might render potential evidence inaccessible when comparing theories. And because it seems to filter information . Even with one’s gaze fixed, covert attention can shift among locations, features, and objects. In such cases, the implications for perception’s epistemic function and the perception-cognition relation are less clear and more controversial. One example: when attentional effects on perception are less obvious, so are their potential biasing effects on belief—whether malign (the neglect of contrary evidence in confirmation bias) or beneficial (when attention prevents us from missing what is most relevant). Another example, which will play a larger role in our discussion: because the mechanisms of covert attention seem more bound up with perceptual processing itself, a cognitive influence upon them appears to amount to a direct effect on perception in a way that cognition’s effects upon overt attention do not.But the case at hand is particularly unsubtle. In other cases, one’s eyes can move in perceptually consequential ways without one’s realizing it, even upon reflection: eye-tracking was required to demonstrate the role of saccades in flipping ambiguous images e.g., . Moreoveattentional effects on perception can amount to cognitive penetration. But talk of cognitive penetration gets cashed out in various ways, so that the answer depends on just what cognitive penetration is supposed to be.Questions concerning cognition’s bearing on perception are often framed in terms of the cognitive penetrability or impenetrability of perception. Applied to our topic, the question is thus whether cognitively driven In what follows, we approach the question using Zenon Pylyshyn’s characterization of cognitive penetration. It was he who coined the term, but, more importantly, his conception is well-motivated, as we will indicate in a moment. A further justification for our focus is that, although much subsequent discussion has centered on Pylyshyn’s claims, his resources for precluding attentional effects from the purview of cognitive penetration have not been fully explored or exploited either by Pylyshyn himself or his other defenders.Pylyshyn’s concern is the degree to which visual perception is “continuous” with cognition. More specifically, he asks whether early visual states interact with cognitive states in the way cognitive states do with one another—in particular, by mirroring rational relations. Early vision would be cognitively penetrated, on his view, if “the function early vision computes is sensitive, in a semantically coherent way, to the organism’s goals and beliefs” , p. 343.We agree that, when cognitive penetration is understood in Pylyshyn’s way, cognitively driven attentional effects on perception do not amount to cognitive penetration—but not for the reason Pylyshyn emphasizes. Pylyshyn maintains that attentional effects occur either before or after early vision and thus do not directly affect early vision itself. Critics have focused on this claim, replying that in fact attention is bound up with perceptual processes at all levels. This in part accounts for a rising tide of attention-based cognitive penetrability claims e.g., . But thePylyshyn defines it: first, it is among the various interesting questions; and, second, considering questions of cognitive penetrability, including what cognitive penetrability should be, is a useful strategy for delineating the various interesting questions, even if it is a ladder one then throws away.But are the significant questions best framed in Pylyshyn’s terms? We conclude by considering other conceptions of cognitive penetration advanced in the literature, some of which do and some of which do not count cognitively driven attentional effects on perception as cognitive penetration. We consider as well how one might decide among them. In the end, we advocate a kind of pluralism, suggesting that there may be no one question of cognitive penetrability, but a variety of interesting successors—and so no one answer to the question concerning attention with which we begin. Pylyshyn’s conception is motivated, but others may be as well. Of course understanding the various ways cognition and perception interact and their upshot is more important than determining if there are phenomena worthy of Pylyshyn’s label. But this conclusion does not undermine the interest of our earlier exploration of attention and cognitive penetration as To see why Pylyshyn holds that cognitively driven attentional effects on perception do not amount to cognitive penetration (and how else it might be defended), we should first clarify his conception of cognitive penetration. A few remarks concerning the relevant kind of attention will also prove useful.source of would-be cognitive penetration—thus comprise for Pylyshyn the so-called propositional attitudes. The relevant target of his impenetrability claim is not perception tout court, which he claims is cognitively penetrable . But views vary as to what counts as cognition, perception, and causing in the right kind of way. These differences matter for whether attentional effects can count as cognitive penetration. Pylyshyn, we saw, is concerned with whether “the function early vision computes is sensitive, in a semantically coherent way, to the organism’s goals and beliefs.” As he also puts it, cognitive penetration requires that early vision “can be altered in a way that bears some logical relation to what the person knows;” an instance of cognitive penetration must “alter the contents of perceptions in a way that is logically connected to the contents of beliefs, expectations, values, and so on” , p. 343.netrable , p. 344,netrable , p. 344.passim) to the cognitive states. The cognitive states must exert their influence because early vision’s computations take their contents into account by operating over them, not just because the cognitive states have effects on other states over which early vision computes. In this sense, the influence must be direct. Second, the contents of the cognitive states and the contents of the affected early vision states must stand in a relation of semantic coherence—or, as he also puts it, a logical or rational relation:Finally, for the causal effect of cognition on early vision to count as the “right kind,” the representational contents of the cognitive states and of the affected early vision states must be related in a way that satisfies two conditions. First, early vision must itself have “access”  as rational because, however, suboptimal they may be by some normative criterion, they do not transform representations in a semantically arbitrary way: they are in some sense at least quasi-logical. This is the essence of what we mean by cognitive penetration: it is an influence that is coherent or quasi-rational when the meaning of the representation is taken into account  distinction need not rest solely upon this discontinuity. For example, one might also differentiate perceptions and cognitions by their relative stimulus-dependence—more specifically, whether it is their function to represent the here and now  or internal  . Our focl search . . Because endogenous cues must be understood, they achieve their attentional effects by engaging mechanisms and cortical areas different from those required for exogenously driven attentional effects; and there is a corresponding difference in time-course: 300 ms from endogenous cue to attention shift, compared to a 100–120 ms peak for exogenous cues . Howevern itself . That saspecial question of whether cognitively driven attentional effects on perception brought on by pre-stimulus cueing  count as cognitive penetration—that is, nothing further to ask beyond whether cognitively driven attentional effects on perception count as cognitive penetration more generally. This turns out to be the case given Pylyshyn’s conception of cognitive penetration: what brought about the cognitively driven attentional effect will be irrelevant to the considerations we adduce. 2Finally, cases of covert attention can also be classified by their object—i.e., what one attends to. Work over the last few decades typically distinguishes spatial, feature-based, and object-based attention . . But because they involve no direct effect on early visual processing itself, they do not exhibit a way “the function early vision computes is sensitive, in a semantically coherent way, to the organism’s goals and beliefs.”Pylyshyn maintains that cognitively driven attentional effects—whether overt or covert—do not provide examples of cognitive penetration of early vision. His main argument is that attentional effects either help determine the inputs to early vision or help select from among its outputs.cortical levels leave little space for an attentionally insulated stage of early vision.  computational stages, and it is the latter with which he is concerned. However, subsequent attention research has arguably trended towards a convergence of behavioral and neurophysiological data that shifts the burden onto anyone who would defend Pylyshyn’s claim that attentional effects are external to early vision. As Critics respond that attentional effects are found at all levels, or stages, of processing. Thus, either they occur in early vision or, if early vision is to be insulated from them, there seems nothing substantial left for early vision to be. Talk of levels can be cashed out in various ways.  Initially, there was a great deal of interest in categorizing mechanisms of vision as pre-attentive or attentive . The interest in that distinction has waned as many studies have shown that attention actually affects tasks that were once considered pre-attentive, such as contrast discrimination, texture segmentation and acuity…. this review focuses on the effect of attention on basic visual dimensions where the best mechanistic understanding of attention to date has been achieved, such as contrast sensitivity and spatial resolution [… and …] motion processing …. due to the existence of models of these visual dimensions, as well as to the confluence of psychophysical, single-unit recording, neuroimaging studies, and computational models, all indicating that attention modulates early vision.inter alia within early vision.  Note that an “all levels” claim can affirm that the fundamental function of attention is to cull inputs. This is a natural idea whose mechanisms are becoming better understood. , this involves there. If the case is to satisfy Pylyshyn’s criteria for being cognitively driven, the subject will come to have an intention or other action-directed attitude to attend there. She will do this on the basis of such other attitudes as her belief that she has been instructed to attend there, her desire to cooperate, etc. Our suggestion is that these attitudes generate what we might call an attentional command to attend there, which—on a causal-computational account—would exert its influence on perceptual processing, affecting perceptual content (at least on the common view suggested by Carrasco’s work and others’—we put aside here Schneider’s animadversions). If the ascription of this attentional command seems fanciful, consider that it is common for computational models of perceptual attention to include attentional parameters that weight the effect of sensory signals . The decision to attend can spring wholly from within (we consider such a case below), but in a typical experiment the subject responds to an endogenous cue—what is in effect an instruction from the experimenter. For example, if the cue is an arrow pointing up or the word ‘up,’ it is an instruction to attend ls e.g., ). ‘Atteneffect on perception would not be. We can think of the effect either as the result brought about or as the bringing about of the result. In the latter sense, the attentional effect consists in the attentional command exerting its influence and thereby affecting perceptual content . In the former sense, it is just the resulting perceptual state (or perhaps some aspect it would otherwise not have had). Either way, the attentional effect would not be directly generated by cognitive states. Moreover, consider the state that is directly affected—the attentional command. Though it is perhaps (if we deny it cognitive status) a representational state in perception, it is not itself a perceptual state, at least in the sense of a state whose function is to represent the here and now. Thus, cognition’s direct effect on it does not constitute cognitive penetration of perception.Now, if the directness aspect of Pylyshyn’s criterion is to be satisfied, perception must have access to and operate over relevant cognitive states: the values of cognitive states must be among the inputs to perceptual processes. One way to defend Pylyshyn’s cognitive impenetrability claim, then, is to argue that (1) the attentional command is not itself a cognitive representation, and (2), although the attentional command plays a role in perceptual processing, the attitudes that generate it do not. The attitudes that generate the attentional command are thus not accessed, and the attentional command is not cognitive; so, no cognitive state is accessed. Perception, by not accessing the cognitive states themselves, would thus not be in that sense sensitive to them; it would only feel the causal effect of those states. We could still say, with Perhaps, when all is said and done, this is correct. But it might not be the most convincing way to defend Pylyshyn’s position. For it is unclear on what basis one can compellingly persuade a proponent of cognitive penetrability that the attentional command is not a cognitive representation. In particular, to base one’s case on the fact that it interacts with perceptual representations would just beg the question: that perceptual processes can have access to cognitive states is precisely what a proponent of cognitive penetration in Pylyshyn’s sense claims.is considered a cognitive state, its influence on perception runs afoul of the semantic coherence constraint—so that cognitive penetrability is blocked whichever status one assigns the attentional command. Recall that the semantic coherence constraint requires that the content of the accessed cognitive state bear an inferential relation to the content of the resulting perceptual state. Attending may exert a causal effect on what one sees. But it does not provide an epistemic basis for it. Here a comparison with turning on a light is appropriate  on color perception  and the resulting perception .treats the belief as evidence for what she sees. This point can be developed in terms of directness: the visual system does not itself access, and so does not take into account, the person’s belief that something red is there; it is just influenced by the action command that in part results from the belief, given how one reasoned what to do. Moreover, the worries raised above about appealing to directness do not apply here: it is contentious to deny that the action command is a cognitive state, but less so to deny that the belief that helps generate the action command in a case like this is not itself accessed by early vision—at least insofar as the belief’s attentional effect is concerned (we return to this caveat in discussing attention and expectation below).But even though the belief in part causes the perception and their contents seem to stand in an appropriate relation, it is not the case that the perceiver or her visual system also not satisfied in this case. Consider the distinction between one claim’s providing a reason for another and one claim in fact being the reason for which someone upholds a claim. 6 If we may apply an analogous distinction in theorizing about the visual system, then we might suggest that semantic coherence requires not just that the cognitive state in part cause the perception and that as a matter of fact there be a semantic relation between their contents, but that the content of the former be part of the basis upon which the content of the latter is generated. This might seem to eliminate the need to advert to directness in replying to such cases after all. But whether this is so depends on what precisely providing a basis requires. A natural cashing out would require directness: being able to access and operate over the cognitive state. If so, this formulation of semantic coherence would simply build in directness. Note though that, even if semantic coherence were construed broadly to include directness, it would not collapse the two constraints: semantic coherence would still go beyond directness. What we have seen is that attentional parameters in visual computations provide an example of how representations can be accessed and operated over without their role in the computation being appropriately inference-like in Pylyshyn’s sense. Otherwise put, they show that, even though a computational transition might itself be deemed an inference, or inference-like, not all elements of the computation need be (quasi-)reason-giving. Attentional weights affect computations in a different way.Perhaps one may argue that in fact the semantic coherence constraint, properly understood, is f = p—where ‘s’ represents the sensory signal, ‘a’ the attentional command , and ‘p’ the resulting perceptual state.7 This introduces a variety of candidate loci for cognitive penetration, in part depending on whether the attentional command is a cognitive state or not. The candidates are: the attitudes’ effect on the command, the command’s effect on the perception, and the attitudes’ effect on the perception. But the attentional command does not stand in the appropriate semantic relation to the resulting perceptual state for it to penetrate perception. And if one maintains further—albeit contentiously—that the attentional command is not a cognitive state, then it is not even a candidate source of penetration. The relation of the generating attitudes to the attentional command does satisfy the semantic criterion. But this is irrelevant if the attentional command is itself a cognitive state and so not a candidate object of penetration. And if the attentional command is not a cognitive state, still, it is not a perception (and thus not a candidate object of cognitive penetration), even if it is a representation in perception in the sense of being operated over in perceptual processing. Finally, though the attitudes that generate the attentional command can sometimes have reason-giving content relative to the resulting perceptual state, in such cases the directness requirement is violated, since perceptual processing, so far as the attentional effect is concerned, does not access—in that sense is not sensitive to—the content. Let us take stock. We suggest that, for cognitively driven attentional effects on perception to amount to cognitive penetration, there must be propositional attitudes that generate an attentional command. The attentional command finds a place in computational models of perceptual processing along the following highly schematized lines: Cognitively driven attentional effects on early vision thus do not provide examples of cognitive penetration in Pylyshyn’s sense. But not for the reason he emphasizes. Even if there are attentional effects that do not occur before or after early vision, they still fail to satisfy Pylyshyn’s requirements—either of directness or of semantic coherence.We can sharpen these points by differentiating our defense from sans sensation—is not cognitively penetrated. Drawing in part upon Lamme and colleagues  in such cases is completely independent of why you attended that way. Having the lights turned off will have the same effect on visual perception regardless of why they were turned off, including whether you turned them off intentionally or accidentally; in both cases it’s the change in the light doing the work, not the antecedent intention. And in similar fashion, attention may enhance what is seen regardless of the reasons that led you to deploy attention in that way, and even whether you attended voluntarily or via involuntary attentional capture; in both cases, it’s the change in attention doing the work, not the antecedent intention  relative to the resulting perceptual state. That the same attentional command could have been otherwise generated is irrelevant, so far as semantic coherence is concerned. But these alternatives do matter for establishing indirectness, which is thus what Firestone and Scholl’s focus on the irrelevance of what caused the attentional change must be about. So, there is a distinction  and a further requirement for cognitive penetration (semantic coherence) that Firestone and Scholl omit.It may seem otherwise, since they speak of sensitivity to content. But reflection on their argument makes it clear they have in mind directness, not semantic coherence. Consider a case where I in fact come to believe X by inferring it from Y, but I could have acquired belief X via hypnosis. That I We conclude by replying to two objections. According to the first, attention should be assimilated to expectation; and, once it is, cognitively driven attentional effects, recharacterized in a Bayesian framework, seem to satisfy Pylyshyn’s requirements. According to the second, we need not stick with Pylyshyn’s characterization of cognitive penetrability in any event; and, on some other, well-motivated conceptions, cognitively driven attentional effects can indeed amount to cognitive penetration.Above, we considered the objection that covert attention does not involve a distinct faculty intermediate between cognition and perception. We responded by arguing that, nonetheless, one may distinguish between an attentional command and attentional effects—adding that attentional weightings, common in computational models, are naturally construed as attentional commands. This restored a notion of attentional cause without reifying an attentional faculty.It may be replied that this does not take sufficiently seriously the claim that attentional effects are a by-product of perceptual processing and do not involve attentional causes at all . The ‘by10 Replacing attentional commands with expectations would thus both remove the barrier to directness and guarantee the satisfaction of semantic coherence.If all attentional effects could be accounted for in this way, the model would require no specifically attentional parameters. For example, rather than a command to attend this much to this location, there might be an increased expectation that the target will be there. Moreover, not only would the expectation cause the attentional effect, it would do so because perception would take it into account in (quasi-) inferentially generating its output.early vision, were in fact cognitive states (beliefs about the future). Second, given recent debates concerning the intended or appropriate Marrian level of Bayesian models  expectations. But the reintroduction of attentional parameters—supposing such models are accepted—argues for a natural divide among phenomena. On such a view, effects not explained attentionally are not attentional effects after all. This might seem a Pyrrhic victory, if the non-attentional expectation effects demonstrate there is cognitive penetration in any event. But this paper is not a defense of cognitive impenetrability tout court, only of the non-penetrability of cognitively driven attentional effects. It remains a question of course whether there is expectation-based cognitive penetration—recall the other issues mentioned above. But if there is, it is important to distinguish it from cognitively driven attentional effects. We want to know not just whether there is cognitive penetration, but also, if there is, the details of how it does and does not occur.It may be replied that this defense of Pylyshyn fails even if only Finally, Pylyshyn’s characterization of cognitive penetration is not the only one. Some others also preclude attentional effects. For example, 12 … perceptual experience is cognitively impenetrable if it is not possible for two subjects (or one subject at different times) to have two different experiences on account of a difference in their cognitive systems which makes this difference intelligible when certain facts about the case are held fixed, namely, the nature of the [effect of the] proximal stimulus on the sensory organ, the state of the sensory organ, and the location of attentional focus of the subject. , p. 2912But some alternative characterizations do not preclude attentional effects. Which conception of cognitive penetration should we use? Which gets the phenomenon right, or marks an important joint, or is the most fruitful? In particular, is it Pylyshyn’s? A tempting reply is that ‘cognitive penetration’ is a technical term, which Pylyshyn coined; so, how it could he fail to get it right? But someone can put their finger on something without quite articulating what matters most. Indeed, the 1999 formulation on which we have focused is itself a modification of Pylyshyn’s earlier statements. (See 13pace14But an alternative approach, which Stokes mentions but does not develop, would consider the consequences for various debates one at a time, instead of attempting to find a single characterization of cognitive penetrability that fits them all cf. . PylyshyThere are many phenomena and questions of interest here. We can be pluralists about our interests. As for the label ‘cognitive penetrability,’ since discussion has proceeded in several directions, we can be pluralist about that as well, so long as we are clear. This does not mean that any characterization of ‘cognitive penetrability’ is as good as another. Some may have no interest at all. Which do will get sorted out in the light of further investigation, theoretical and empirical. We have argued that Pylyshyn’s question is of interest and that his answer, regarding attentional effects, is correct—although not for the reason he emphasizes.The author confirms being the sole contributor of this work and approved it for publication.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The obtained HNH reduced graphene oxide (HNH-rGO) was characterized by X-ray diffraction (XRD), scanning electron microscope (SEM), Raman spectroscopy, X-ray photoelectron spectroscopic (XPS) and Fourier transform infrared spectra (FTIR). The results demonstrated that GO was successfully reduced to graphene and the surface of HNH-rGO was grafted with HNH. The interlayer space was increased from 0.751 nm to 1.921 nm, and its agglomeration was much more attenuated compared with GO. HNH-rGO/polypropylene and graphene/polypropylene composites were synthesized through melt-blending method. The viscosity was enhanced with increased addition of graphene and surface modified graphene demonstrated stronger rheological behavior improving effect than the untreated graphene. Since t in 2004 , liquid  in 2004 , superca in 2004 ,7, polym in 2004  as well  in 2004 . This is in 2004 ,11. To p in 2004 ,13,14,15 in 2004 ,17, unzi in 2004 ,19,20, e in 2004 ,22 and c in 2004 ,24 and s2 hybridization in the microstructure of graphene so that the electrical and thermal conductivities may decrease. Given that via noncovalent modification the interactions between graphene and the modifier substances are weak which is unbenefited for load transfer, covalent modification is obviously a better choice.It is its many intriguing properties that attract plenty of researchers to study graphene and make graphene polymer nanocomposites a hotspot in composite materials field. However, the strong intermolecular force between graphene sheets restricts the homogeneous dispersion within the polymer matrix. To avoid agglomeration of graphene sheets in a polymer matrix, modifications of graphene are urgently needed as essential methods. Covalent and noncovalent modifications are two approaches to modify and functionalize graphene . Covalen4 or other reductants with organic or inorganic functional groups [In a typical oxidation-reduction method, GO is obtained from graphite via oxidation by a strong oxidant like concentrated sulfuric acid and grafted with hydrophilic functional groups, such as –OH, epoxide, –COOH. Then GO is reduced to graphene by hydrazine hydrate, hydroquinone, NaBHl groups ,27. The l groups . Jang etl groups . Yoo et l groups . Goods el groups . Kumar el groups . Tang etl groups . Wang etl groups . Shen etl groups . Some rel groups ,37,38. Hl groups ,40,41 wil groups . So the l groups  demonstrIn this article, a one-step reduction and surface modification procedure of GO by a new reductant 3-hydroxy-2-naphthoic hydrazide (HNH) and synthesis of graphene modified polypropylene nanocomposites were prepared. The process was easy to operate and the interlayer space of the obtained HNH reduced graphene (HNH-rGO) was increased to 1.921 nm compared with 0.751 nm of GO. It was demonstrated that, as the amount of graphene filler increased, the rheological behavior of composites was changed. Moreover, surface modified graphene demonstrated a stronger viscosity improving effect than the untreated graphene.Graphene used in this study was supplied by Nanjing XF NANO Materials Tech Co., Ltd., Nanjing, China. Graphene oxide and polypropylene (PP) were purchased from Aladdin Company, Shanghai, China. 3-Hydroxy-2-naphthoic hydrazide (HNH) and all the other chemical materials were obtained from Sigma-Adrich . All chemicals were used without further treatment.HNH was used to reduce and modify GO powder in one step and its chemical structure is showed in In a typical synthesis procedure of HNH-rGO/PP and G/PP composites, 30 g PP and different amount of HNH-rGO or graphene were mechanically mixed in a beaker. After mixed homogeneously, the mixture was put into a torque rheometer and stirred at 180 °C for 5 min to obtain the composites.X-ray diffraction (XRD) patterns were recorded from 3°–60° (2θ) using X-ray diffractometer  with a Cu Kα radiation source (k = 1.5406 Å). Scanning electron microscope (SEM) observation was performed on Zeiss Merlin Compac . Raman spectra were obtained on LabRAM HR800 spectrometer  using a 488 nm laser. X-ray photoelectron spectroscopic (XPS) characterizations were operated on Thermo Fisher ESCALAB 250Xi . Fourier transform infrared spectrum (FTIR) measurements were carried out with the KBr pellet method on Perkin-Elmer spectrometer .The XRD pattern of GO, HNH and HNH-rGO samples were presented in −1) is due to the doubly degenerate zone center Eg2 mode and originated from the vibration in plane of sp2 hybrid carbon atoms. The 2D (2700 cm−1) peak is the second order of zone-boundary phonons. The defects in graphene will be reflected on the D peak (1350 cm−1). As presented in −1) compared with GO shifted closer to graphene (1563 cm−1), which indicated a successful functionalization of reduced GO and a recombination of sp2-hybridized graphitic network at mean time. Besides, the intensity ratio of D/G peaks that generally imply the defect concentration of graphene and the defect concentration of graphene can be calculated by: D/IGI ratio of HNH-rGO was 0.46 smaller than that of GO (0.93), so the surface defects of HNH-rGO was reduced by half and the sp2-hybridized degree was improved. However, the D/IGI ratio of HNH-rGO was a little bigger than that of graphene (0.09) and the authors’ previous research (0.29) [L4(IDIG) . The resh (0.29) , mainly h (0.29) . In the −1, C–O–C stretching vibration at 1044 cm−1, stretching vibration of aromatic C=C at 1587 cm−1, and the stretching vibration of hydroxyl groups was observed as a broad strong band centered at 3364 cm−1. After being reduced and modified by HNH, the intensities of hydroxyl groups and C–O–C stretching vibration were dramaticlly decreased as can be seen in −1, carbonyl of acylamino at 1634 cm−1, C–N at 1175 cm−1 and aromatic ring at 1450 cm−1 gave adequate evidences to the successful modification that the molecular chain of HNH was grafted onto the surface of rGO. Besides, the peaks at 1560 cm−1 and 739 cm−1 corresponded to stretching vibration of aromatic C=C in graphene and the ortho-disubstituted aromatic ring in HNH, respectively.Fourier transform infrared spectrum (FTIR) is an effective method to detect organo-functional group and can give proof to the successful modificaton. As displayed in In consequence, through a one-step reduction and covalent modification method by a new reductant HNH, GO was successfully reduced and modified into HNH-rGO grafted with the molecular chain of HNH. The interlayer space of HNH-rGO increased from 0.751 nm to 1.921 nm so that the Van der Waals’ force was decreased and the agglomeration was ameliorated. The XRD result and decrease of O content from 17.19% to 7.57% provided valid evidences for the successful reduction of GO. The appearances of stretching vibration of N–H, carbonyl of acylamino, C–N and aromatic ring provided adequate reason for the successful modification. In contrast with HBS, HNH exhibited a better effect on enhancing interlayer space. HNH-rGO/PP composites performed with better rheology property than graphene/PP composites. This study revealed that HNH-rGO was a potential filler to obtain homogenous polymer nanocomposites coatings with preferable rheology behavior.


Nb C3 and E2 showed specific antigen binding and beneficial biodistribution. Through the use of CRISPR/Cas9 PD-L1 knock-out TC-1 lung epithelial cell lines, we demonstrate that SPECT/CT imaging using Nb C3 and E2 identifies PD-L1 expressing tumors, but not PD-L1 non-expressing tumors, thereby confirming the diagnostic potential of the selected Nbs. In conclusion, these data show that Nbs C3 and E2 can be used to non-invasively image PD-L1 levels in the tumor, with the strength of the signal correlating with PD-L1 levels. These findings warrant further research into the use of Nbs as a tool to image inhibitory signals in the tumor environment.Blockade of the inhibitory PD-1/PD-L1 immune checkpoint axis is a promising cancer treatment. Nonetheless, a significant number of patients and malignancies do not respond to this therapy. To develop a screen for response to PD-1/PD-L1 inhibition, it is critical to develop a non-invasive tool to accurately assess dynamic immune checkpoint expression. Here we evaluated non-invasive SPECT/CT imaging of PD-L1 expression, in murine tumor models with varying PD-L1 expression, using high affinity PD-L1-specific nanobodies (Nbs). We generated and characterized 37 Nbs recognizing mouse PD-L1. Among those, four Nbs C3, C7, E2 and E4 were selected and evaluated for preclinical imaging of PD-L1 in syngeneic mice. We performed SPECT/CT imaging in wild type versus PD-L1 knock-out mice, using Technetium-99m ( Al. Al6 tagcontrols . Protein−10 m2/s depending on the theoretical Nb molecular weight. The PE dilution resulting in the largest difference in slope between the two flow speeds was used to calculate the Nb concentration using Biacore Evaluation software.All measurements were performed on a Biacore T200 device  at 25°C and using Hepes-buffered saline  as running buffer. All recombinant proteins were dissolved to 10 ug/mL in 10mM Na-acetate pH 5.0 for immobilization on a CM5 sensor chip using linkage chemistry with 1-(3-(dimethylamino)propyl)-3-ethylcarbodiimide (EDC) and N-hydroxy-succinimide (NHS). Unreacted EDC-NHS linkers were blocked with 1M ethanolamine-HCl. For all measurements, SPR signals in the flow cell with immobilized protein were subtracted with those in a flow cell that underwent the same manipulations but where recombinant protein was omitted, to obtain specific binding signals . For CFCA, recombinant mouse PD-L1 protein was coupled to 9920 RU, for all other measurements between 650 and 900 RU proteins were coupled. For all measurements and between each cycle, chips were regenerated twice with 0.5M NaCl, 15 mM NaOH, each time for 10 sec at 40 μl/min. CFCA was used to estimate the concentration of Nb in each PE and was performed according to manufacturer's instructions. Briefly, 3 different dilutions of PEs  were run for 35 sec at 5 and at 100 μL/min on a chip with high mouse PD-L1 protein densities and RUs were recorded. The Nbs' diffusion coefficient was calculated using an online tool provided by the company, assuming a protein globular shape, and ranged between 1.0 and 1.3ED was calculated by fitting the obtained sensorgrams to theoretical curves, assuming 1-to-1 binding geometries, using Biacore Evaluation software.The estimated Nb concentrations in the PEs ranged between 13 and 4900 nM and was usually around 150 nM. Nbs, either in PEs or as purified proteins, were tested for affinity on immobilized mouse or human PD-L1 protein in SPR. To this end, 9 different Nb dilutions were allowed to bind to the target protein for 120 sec and dissociation was monitored for 160 sec. The equilibrium dissociation constant KMice deficient in PD-L1 expression (referred to as PD-L1 knock-out mice) were bred in-house, C57BL/6 mice were supplied by Charles River Laboratories (France) at 6 weeks of age. All experiments were performed in accordance to the European guidelines for animal experimentation under a License LA1230214. Experiments were approved by the Ethical Committee for the use of laboratory animals of the Vrije Universiteit Brussel (15-214-1).T.C. Wu  kindly provided the mouse lung epithelial cell line TC-1. TC-1 cells were cultured in RPMI medium, consisting of RPMI 1640 medium (Sigma-Aldrich) supplemented with 10% FCI serum (Harlan), 2 mmol/L L-glutamine , 100 U/mL penicillin, 100 μg/mL streptomycin , 1 mmol/L sodium pyruvate and non-essential amino acids (Sigma-Aldrich). Lentiviral vectors harboring the mouse PD-L1 gene, a short hairpin RNA (shRNA) targeting PD-L1 or a PD-L1 targeting guide RNA and Cas9 were used to generate TC-1 lung epithelial cells in which PD-L1 was knocked-in, knocked-down or knocked-out respectively. Lentivirus generation is described below.Human embryonal kidney (HEK) 293T cells were purchased from the American Type Culture Collection (ATCC/LGC standards) and were cultured in Dulbecco's modified Eagle's medium (Sigma-Aldrich) supplemented with 10% FBS (Harlan), L-Glu and PS. Lentiviral vectors harboring the mouse or human PD-L1 gene were used to generate HEK293T cells expressing mouse or human PD-L1.B16 cells were purchased from ATCC and cultured in DMEM medium, consisting of Dulbecco's modified Eagle's medium (Sigma-Aldrich) supplemented with 10% FBS (Harlan), L-Glu, PS and 50 μM β-mercaptoethanol. Lentiviral vectors harboring shRNA targeting PD-L1 were used to generate a B16 cell line negative for mouse PD-L1 (PD-L1-). Parental B16 cells served as a mouse PD-L1 positive cell line (PD-L1+).The plasmids pCMVΔR8.9 and pMD.G were a gift from D. Trono . The transfer plasmid encoding human PD-L1, pHR’-huPD-L1 was previously described . The plaExpression of PD-L1 on wild type or lentivirally modified HEK293T, TC-1 or B16 cells was evaluated using an antibody specific for mouse or human PD-L1. Binding of purified His-tagged Nbs or HA-tagged Nbs in PEs to wild type or lentivirally modified HEK293T cells was detected with respectively an anti-His-tag antibody or an anti-HA-tag antibody followed by an anti-mouse IgG antibody. Single cell-suspensions of spleens, lymph nodes, tumors and brown adipose tissue were prepared and expression of PD-L1 on immune cells versus non-immune cells was evaluated using an antibody specific for mouse CD45 and an antibody specific for mouse PD-L1. Cells were acquired on the LSRFortessa flow cytometer (BD Biosciences) and data were analyzed with FACSDiva (BD Biosciences) or FlowJo (Tristar Inc.) software.5 TC-1 wild type, PD-L1 knock-in, knock-down or knock-out cells. When indicated, mice were injected one day before tumor inoculation with 100 μg depleting anti-CD8 antibodies (clone 2.43) or isotype matched control antibodies (LTF-2). The injections were repeated every three days. The antibodies were purchased from BioXcell. The tumor volume was measured thrice a week using an electronic caliper. The tumor volume was calculated using the following formula: (length × width2)/2.C57BL/6 wild type and PD-L1 knock-out mice were injected subcutaneously with 5 × 106-tag with 99mTc-tricarbonyl intermediate [99mTc(H2O)3(CO)3]99m, which was synthesized using the Isolink® labelling kit . The 99mTc-Nb solution was purified on a NAP-5 column  pre-equilibrated with PBS to remove unbound (99mTc(H20)3(CO)3)+ and finally filtered through a 0.22 μm filter (Millipore) to remove aggregates. The labeling efficiency was determined both directly after labeling and after purifications by instant thin-layer chromatography (iTLC) with 100% acetone as the mobile phase. Mice were injected intravenously with 100 to 200 μL of 45 to 155 MBq of 99mTc-labeled Nbs (10 μg), one hour prior to pinhole SPECT-micro-CT imaging. Imaging was performed as described [e.cam180; Siemens Medical Solutions), mounted with 2 multipinhole collimators . Micro-CT was performed using a dual-source CT scanner  with 60 kV and 615 mA at a resolution of 83 μm. CT images were reconstructed using filtered back projection . SPECT images were reconstructed using an iterative reconstruction algorithm (ordered-subset expectation maximization) modified for the 3-pinhole geometry and automatically reoriented for fusion with CT images based on six 57Co landmarks [The Nbs were labeled as described by Xavier et al . Brieflyescribed . Total bP < 0.05; **P < 0.01; ***P < 0.001.Results are expressed as mean ± standard error of the mean. A non-parametric Mann-Whitney U test or One-Way-ANOVA followed by Bonferroni multicomparison test was carried out to compare data sets. Sample sizes and number of times experiments were repeated are indicated in the figure legends. The number of asterisks in the figures indicates the statistical significance as follows: *


We observed that p31-43 exacerbates kainate neurotoxicity in epilepsy models, through the involvement of the enzymatic activity of transglutaminases. Moreover, electrophysiological recordings in CA3 pyramidal neurons of organotypic hippocampal slices show that p31-43 increases the inward current induced by kainate, the average sEPSC amplitude and the total number of evoked action potentials when applicated alone, thus suggesting that p31-43 is able to influence CA3-CA1 neurotransmission and can potentiate postsynaptic kainate receptors. Our results suggest a possible mechanism underlying the relationship between GRD and epilepsy through a potentiation of kainate-induced neurotoxicity and links the toxic effects of gluten to epilepsy.Many neurological disorders of gluten-related diseases (GRD), not directly referable to the gastrointestinal tract, have been reported in association with celiac disease (CD), including ataxia, neuropathy and epilepsy. In particular, people with epilepsy diagnosed with CD seems to be characterized by intractable seizure. In these patients, gluten restriction diet has resulted in a reduction of both seizure frequency and antiepileptic medication. Many hypotheses have been suggested, however, molecular mechanisms that associates GRD and epileptogenesis are yet unknown. In this study, we examined the effects of the toxic gliadin peptide 31-43 in  In particular, people with epilepsy seem to be diagnosed with CD far more often than the general population. Data suggest that up to 22% of patients with CD develop neurologic or psychiatric dysfunction2, and as many as 57% of people with neurological dysfunction of unknown origin test positive for anti-gliadin antibodies3. It is interesting to notice that in “intractable epilepsy”, gluten restriction diet has resulted in a reduction of seizure frequency with a decrease in antiepileptic medication needed to control intractable seizure in humans4. Unfortunately, there is no evidence on the casual relation between epilepsy and GRD and it remains unclear whether gluten contributes to the pathogenesis of these disorders or whether it represents an epiphenomenon. There are many hypotheses to explain this correlation and possible mechanisms have been suggested, such as: autoimmune mechanisms5, malabsorption6 and gluten toxicity7.The symptoms of Celiac Disease (CD) or gluten-related diseases (GRD) are mostly characterized by digestive symptoms, which are often the first perceived signs of gluten intolerance. However, converging evidences suggest that the gluten-mediated immune response is frequently associated with neurological and psychiatric manifestations, including ataxia, neuropathy and epilepsy8. TG2, particularly notable for being the autoantigen in CD, is the most widely expressed and abundant member of the transglutaminase family9. The anti-TG2 antibodies are used as serological tests for identifying CD patients, but have been recently implicated in the pathogenesis of several neurodegenerative diseases10. Another enzyme of the transglutaminase family primarily expressed in the central nervous system is transglutaminase 6 (TG6)11. Specifically, it was reported that anti-TG6 antibodies are gluten-dependent and appear to be a specific marker for neurologic manifestations. Indeed, TG6 antibodies were identified in immune-mediated ataxia in patients with gluten sensitivity thus suggesting a critical role for TG6 in cortical and cerebellar neurons12.Transglutaminases (TGs) are a calcium-dependent enzyme of the protein-glutamine γ-glutamyltransferases family which catalyze the cross linking of a glutaminyl residue to a lysyl residue. To date, at least eight different human TGs have been identified and recently their roles in several diseases have been investigated13 and has been shown to be toxic both in in vitro and in vivo tissues obtained from patients with CD15. Moreover, the p31–43 is able to initiate both a stress and an innate immune response with interleukin-15 (IL-15) as a major mediator in celiac intestine16. However, the effect and the molecular mechanisms of toxicity induced by p31-43 in the brain are poorly understood.The gliadin peptide 31-43 (p31–43), is one of the main gliadin peptides that remain undigested by the intestinein vivo and in vitro models of kainate-induced-epilepsy and we observed that p31-43 exacerbates kainate neurotoxicity in epilepsy models, thus suggesting an increased excitotoxic synaptic activity of CA3-CA1 neurotransmission. Furthermore, we evaluated the involvement of the enzymatic activity of transglutaminases.In this research, we studied the effects of gliadin peptide 31-43 in per se (data not shown), in contrast, the administration of p31-43 exacerbates the number and the duration of seizures induced by kainate  with kainate (30 mg/k), p31-43 (30 mg/kg) alone or with the combination of them and the animals were observed for 90 min in order to assess latency, type and duration of epileptic seizures. p31-43 is not convulsive ate Fig.  without ate Fig. . Moreovein vivo results suggest that p31-43 could potentiate the kainate-induced neurotoxicity on CA3 hippocampal neurons. In order to demonstrate our hypothesis, we performed electrophysiological experiments by recording kainate-induced inward current in CA3 pyramidal cells of organotypic hippocampal slices. We observed that p31-43  increases the inward current induced by kainate (0.3 µM) . We exposed CA3 neurons to p31-43 (30 µg/ml) for 5 min and we measured the amplitude and the frequency of sEPSCs during its application. We observed that p31-43 caused a significant shift in the cumulative probability plots on sEPSC amplitude . No effect was observed on the sEPSC frequency  Fig. , indicatin vitro model of epilepsy. To this aim, we exposed organotypic hippocampal slices to 5 µM kainate for 24 h. Under these conditions, the slices underwent selective injury of the CA3 pyramidal cells  to the incubation medium alone . Conversely, the incubation with maize zein, a prolamin protein derived from corn used as control peptide, was not toxic by itself and did not alter kainate-induced CA3 toxicity , thus suggesting that specifically p31-43 was responsible for increased kainate induced-damage.It is still unclear whether a long exposure to p31-43 could be able to cause CA3 neurodegeneration. Therefore, we tested the chronic application of p31-43 in our lls Fig. , which ione Fig.  or durinone Fig. . Accordione Fig. , while ileft panel) but attenuated kainate plus p31-43 CA3 induced-toxicity  .We hypothesize that the toxic effects of p31-43 on kainate-induced neurotoxicity could be mediated by transglutaminases involvement. Therefore, we studied the expression level of TG2 and TG6 proteins after exposure to p31-43 by western blotting technique in homogenates of organotypic hippocampal slices. We observed that the incubation with p31-43 (30 µg/ml for 24 h) significantly increased the expression of TG2 and TG6 Fig. . Therefoin vivo model of epilepsy. Our results show that the gliadin peptide p31-43 does not provoke convulsions per se, while the administration of p31-43 in C57/B mice exacerbates the number and the duration of seizures induced by kainate. In addition, the animals treated with the combination of p31-43 and kainate presented a higher mortality at the end of the experiments compared to animals treated with kainate alone, thus demonstrating the noxious effects of p31-43 on kainate-induced seizure. Our data reproduce what has been widely observed in many clinical case reports that describe a link between epilepsy and CD18. In particular, a specific type of focal epilepsy associated with occipital calcifications was described by Gobbi and co-workers19. This form is characterized by antiepileptic drug-resistant seizures and has been shown to benefit from gluten restriction diet4. Since no animal model mimicking all the key factors predisposing to CD  is currently available, in our in vivo experiments we injected p31-43 i.p. in order to cross the intestinal barrier thus mimicking the altered intestinal permeability of CD.The present study reports, for the first time, the toxic effects of the gliadin peptide 31-43 on kainate-induced seizures in an in vivo, we hypothesized that p31-43 could potentiate the kainate-induced neurotoxicity on CA3 hippocampal neurons, which are the main targets of kainate in the hippocampal region ) as well as the shift in the cumulative probability plots on sEPSC amplitude. These findings indicate that the gliadin peptide induces postsynaptic modifications and suggest that p31-43 can potentiate glutamatergic synaptic transmission influencing the sensitivity of postsynaptic kainate receptors. Additionally, p31-43 provokes also a significant increase in the total number of evoked APs, suggesting that p31-43 is able to increase neuronal excitability that could result in enhanced firing probability following an excitatory stimulus, such as kainate-induced depolarization.To explain the results obtained in our experiments in vitro model of kainate induced CA3 toxicity, which is considered a classical model of temporal epilepsy17. p31-43 do not induce toxicity by itself, when incubated alone for 24 h, while it exacerbates CA3 injury induced by kainate in a dose-dependent manner. Conversely, the incubation with maize zein, a prolamin protein derived from corn used as control peptide, was not toxic by itself and did not alter kainate-induced CA3 toxicity, thus suggesting that specifically p31-43 was responsible for increased kainate induced-damage.Considering that it is still unclear whether a long exposure to p31-43 could be able to cause CA3 neurodegeneration, we tested the chronic application of p31-43 in our 9. Glutamine-rich gliadin peptides are excellent substrates for TG2. Indeed, up to 36% of the glutamine (Gln) residues in gliadin were accessible to modification by TG2. The physiological roles of TG2 are not fully characterized and many basic questions remain unresolved. Conversely, TG2 has been mostly linked to a number of diseases, including inflammatory bowel disease, cancer21, human immunodeficiency virus (HIV) infection22 and neurological disorders10. The TG6 isoform appears to be a specific marker for neurologic manifestations and recently it has been shown that neurodegenerative diseases, such as Alzheimer’s disease, Parkinson’s disease, Huntington’s disease and other polyglutamine diseases are characterized in part by aberrant cerebral transglutaminase activity and by increased cross-linked proteins in affected brains23. To explain our results, we theorized that that two different mechanisms in different time points might exist. Indeed, the early responses are probably due to post-synaptic kainate receptors potentiation induced by p31-43 leading to the observed electrophysiological effects  that may contribute to the potentiation of kainate toxicity. Therefore, we studied the expression level of TG2 and TG6 proteins after exposure to p31-43 by western blotting technique in homogenates of organotypic hippocampal slices. We observed that the incubation with p31-43 significantly increased the expression of TG2 and TG6, supporting our hypothesis according to which p31-43 may determine toxicity by increase glutamate residues by Gln deamination due to the activation or overexpression of TGs. Our theory is also reinforced by the results obtained with maize zein that is a prolamin protein that does not contain glutamine residues and does not provoke toxicity by itself nor alters kainate-induced CA3 toxicity. Our results are supported by Caputo and coworkers which observed that prolonged treatment of human intestinal Caco-2 cell line  with p31-43 increased TG2 protein expression, indicating a non-tissue-specific post-translational mechanism of the gliadin peptide 31-4324. Furthermore, it has been shown that TG6 immunoreactivity is present in the CA3 region, but not in CA1/CA2 or in the dentate gyrus (DG)25 thus supporting our in vitro results in which we observed that p31-43 exacerbates kainate neurotoxicity selectively in the CA3 region of hippocampal slices. Hence, we tested the non-selective TGs inhibitor Z-DON-Val-Pro-Leu-OMe (Z-DON)26 as a possible neuroprotective drug in our system. The addition of Z-DON was not neuroprotective on kainate alone but attenuated kainate plus p31-43 CA3 induced-toxicity. Interestingly, TGs inhibitors were recently proposed for maintaining the integrity of intestinal tight junctions as a way of preventing downstream inflammatory cascades and are also effective in reducing the production of anti-TG2 antibodies when studied in duodenal biopsy cultures from untreated (gluten-containing diet) celiac patients27. Furthermore, a new possible role of TGs inhibitors in the therapy for Huntington’s disease28, Alzheimer’s disease29, Parkinson’s disease30, excitotoxicity and stroke32 has recently emerged.We hypothesized that the toxic effects of p31-43 on kainate-induced neurotoxicity could be mediated by transglutaminases involvement. The role of TG2 in CD has now very well established exerting at least two crucial roles: as a deamidating enzyme of gliadin peptides, that can enhance the immunostimulatory effect of gluten and as a target autoantigen in the immune responsects Fig. . These eIn conclusion, our study associates the toxic effects of gluten to epilepsy. In particular, our findings suggest a possible mechanism underlying the relationship between gluten and epilepsy through a potentiation of neurotoxicity induced by kainate on CA3 hippocampal neurons by p31-43 and the overexpression and activation of neuronal TGs.Experiments and animal use procedures were in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals . The experimental protocols were approved by the Animal Care Committee of the Department of Health Science, section of Pharmacology, University of Florence, in compliance with the European Convention for the Protection of Vertebrate Animals used for Experimental and Other Scientific Purposes (ETS no. 123) and the European Communities Council Directive of 24 November 1986 (86/609/EEC). The authors further attest that all efforts were made to minimize the number of animals used and their suffering.Kainic acid was purchased from Sigma , synthetic peptide p31–43 (LGQQQPFPPQQPY) was purchased from Primm srl, , transglutaminases (TGs) inhibitor Z-DON  was obtained from Zedira GmbH . Propidium iodide (PI) was purchased from Sigma . Tissue culture reagents were obtained from Gibco-BRL  and Sigma .et al.32. C57/Bl6 male mice (30 g)  were used for kainate-induced seizures. Seizure response was assessed by adopting the following scale previously described in Jiang et al., 2015: 0 = normal behavior, 1 = immobile and cleaved up posture, 2 = automatisms, 3 = partial body clonus and shivering, 4 = whole body clonus, rearing and falling, 5 = non intermittent seizure activity, 6 = wild running and tonic seizure, 7 = death. We measured the seizure score including latency to seizure, type and duration of seizures. Data are expressed as the mean ± SEM. All animal procedures were conducted according to the European Community Guidelines for Animal Care. C57/B mice  were randomly divided into 4 experimental groups in order to assess epileptic seizures induced by: i) kainate  (group 1), ii) p31-43  (group 2), iii) kainate plus p31-43  (group 3) and iv) a comparable volume of 0.9% NaCl (group 4).We used the experimental protocol previously described by Muzzi 34. Briefly, hippocampi were removed from the brains of 7- to 9-day old Wistar rat pups , transverse slices (420 µm) were prepared using a McIlwain tissue chopper and then transferred onto 30 mm diameter semiporous membranes inserts , which were placed in six well tissue culture plates containing 1.2 ml medium per well. The culture medium consisted of 50% Eagle’s minimal essential medium, 25% heat-inactivated horse serum, 25% Hanks’ balanced salt solution, 5 mg/ml glucose, 2 mM L-glutamine, and 3.75 mg/ml amphotericin B. Slices were maintained at 37 °C in an incubator in atmosphere of humidified air and 5% CO2 for two weeks. Before experiments all slices were screened for viability by incubating them for 30 min with PI (5 μg/ml); slices displaying signs of neurodegeneration were discarded from the study. After 2 weeks in culture, the slices were exposed to 5 µM kainate for 24 h. Under these conditions, the slices undergo selective injury of the CA3 pyramidal cells, which is considered a classical model of temporal epilepsy17. We have tested the effects of the gliadin peptide 31-43 (10-100 µg/ml) by adding the peptide to the incubation medium during the 24 h exposure to kainate.Organotypic hippocampal slice cultures were prepared as previously reportedTM; Intracellular Imaging Inc., Cincinnati, OH, USA) and subsequently analyzed using the Image-Pro Plus morphometric analysis software . In order to quantify cell death, the CA3 hippocampal subfield was identified and encompassed in a frame using the drawing function in the image software  and the optical density of PI fluorescence was detected. There was a linear correlation between CA3 PI fluorescence and the number of injured CA3 pyramidal cells as detected by morphological criteria36.PI (5 μg/ml) was added to the medium either at the end of the kainate incubation period. Thirty minutes later, fluorescence was viewed using an inverted fluorescence microscope  equipped with a xenon-arc lamp, a low-power objective (4X) and a rhodamine filter. Images were digitized using a video image obtained by a CCD camera  controlled by software  containing (in mM): NaCl 130, KCl 3.5, Na2H2PO4 3, NaHCO3, glucose, MgCl2 1.5 and CaCl2 1.5 at pH 7.4 and oxygenated with 95%O2/5%CO2. Recording microelectrodes were prepared from borosilicate glass  by a Narishige Instruments micropipette puller  (resistance ranging from 3 to 5 MΩ) and filled with internal solution of the following composition (in mM concentrations): K-gluconate 142.5, potassium methylsulfate 20, NaCl 8, Hepes 10, EGTA 0.1, MgATP 2, and GTP 0.2. The pH of the internal solution was adjusted to 7.2 with KOH and the osmolarity was adjusted to 300 mOsm with H2O and sucrose. Recordings were done using a Multiclamp preamplifier  and filtered at 5 kHz. All the data were acquired, stored and analyzed on a PC using the pCLAMP  and GraphPad softwares. Traces were filtered by a digital Gaussian filter . The frequency and peak amplitude of detected events were analyzed using Mini Analysis Program . To evaluate the total synaptic input onto CA3 region, whole-cell voltage-clamp recordings were performed and spontaneous excitatory post-synaptic currents (sEPSCs) were recorded in CA3 region. Moreover, to study the effect of p31-43 on the whole intrinsic excitability, increasing steps of depolarizing current were imposed in current-clamp configuration to CA3 neurons to measure: number, latency, amplitude and threshold of evoked action potentials (APs).The experiments were conducted as previously described in Gerace 37. Total protein levels were quantified using the Pierce  BCA (bicinchoninic acid) Protein Assay. 40 μg of proteins were resolved by electrophoresis on a 8% SDS-polyacrylamide gel and transferred onto nitrocellulose membranes using the transblot TURBO . Blots were probed overnight at 4 °C with the polyclonal rabbit transglutaminase-2 (TG2)  and transglutaminase-6 (TG6) , antibodies all diluted 1:1000. Immunodetection was performed with secondary antibodies ) conjugated to horseradish peroxidase. The reactive bands were detected using chemiluminescence . Quantitative analysis was performed using the QuantityOne analysis software .Cultured slices were washed with cold 0.01 M phosphate-buffered saline, pH 7.4 and 8 slices/sample were gently transferred and dissolved in a tube containing 1% SDS as previously reportedData are presented as means ± SEM of n independent experiments. Statistical significance was evaluated by unpaired Student’s t test, except for Kolmogorov-Smirnov (KS) statistics and PI fluorescence intensities that were evaluated by performing one-way ANOVA followed by Tukey’s w test for multiple comparisons. All statistical analysis were performed using Graph-Pad Prism v. 5 for Windows . A probability value (P) of <0.05 was considered significant.All procedures were approved by the Animal Care Committee of the Department of Health Science, section of Pharmacology, University of Florence.Supplementary Dataset 1