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


Since the discovery of the two-dimensional (2D) carbon material, graphene, just over a decade ago, the development of graphene-based field effect transistors (G-FETs) has become a widely researched area, particularly for use in point-of-care biomedical applications. G-FETs are particularly attractive as next generation bioelectronics due to their mass-scalability and low cost of the technology’s manufacture. Furthermore, G-FETs offer the potential to complete label-free, rapid, and highly sensitive analysis coupled with a high sample throughput. These properties, coupled with the potential for integration into portable instrumentation, contribute to G-FETs’ suitability for point-of-care diagnostics. This review focuses on elucidating the recent developments in the field of G-FET sensors that act on a bioaffinity basis, whereby a binding event between a bioreceptor and the target analyte is transduced into an electrical signal at the G-FET surface. Recognizing and quantifying these target analytes accurately and reliably is essential in diagnosing many diseases, therefore it is vital to design the G-FET with care. Taking into account some limitations of the sensor platform, such as Debye–Hükel screening and device surface area, is fundamental in developing improved bioelectronics for applications in the clinical setting. This review highlights some efforts undertaken in facing these limitations in order to bring G-FET development for biomedical applications forward. The unique properties of graphene, including excellent conductivity, rapid electron transport, large surface area, and biocompatibility [The discovery of Graphene in 2004 by Novoselov and Geim  brought tibility ,2, make tibility . The devtibility . Biosenstibility . For exaRecent advances in the microfabrication techniques have led to the development of next-generation bioelectronic devices, including silicon nanowires ,8,9,10, G-FET biosensors are particularly attractive in point-of-care diagnosis due to their miniaturization, potential for large-scale manufacture at low-cost, rapid and inexpensive assays, and reduced need for skilled personnel. Moreover, G-FET biosensors offer the benefits of high sensitivity, lower detection limits, low cost, and high throughput detection compared to the existing enzyme-linked immunosorbent assay (ELISA), Polymerase Chain Reaction (PCR), and fluorescence methods, which are time consuming and require expensive and complex optical imaging devices and sophisticated image recognition software . It is fThis review is organized to emphasize the recent developments in affinity-based G-FET biosensors. We will briefly discuss the properties of graphene functionalization techniques in the context of bioelectronics in 2sp-hybrised carbon [2/g), a trait which is particularly advantageous in biosensing applications [7 cm2·V−1·s−1 in graphene that has been decoupled from bulk graphite, to be as high as 105 cm2·V−1·s−1 in suspended graphene devices [3 cm2·V−1·s−1 for CVD graphene on a SiO2 substrate. Moreover, graphene material can be manufactured in large quantities and relatively cheaply, therefore making it a suitable substrate for large-scale electronic device manufacturing [Graphene, or single atomic thick carbon, is the first purely two-dimensional (2D) material to be obtained . Graphend carbon . The 2D ications . Graphenications . Experim devices , and aboacturing .K and K’ points in the Brillouin zone. At the point where they meet, depicted by the Dirac voltage (VD) in Vg–IDS measurements, the Fermi level passes across. This Fermi level can be tuned and adapted because of doping by external influences, such as electron deficient (p-doping) or electron rich (n-doping) molecules [D to a more positive voltage (p-doping) or to a more negative voltage (n-doping). The VD can therefore be monitored and utilized as a means of sensing biological molecules. The electronic properties, such as the VD, carrier mobility, and resistance, can be influenced by many external sources, these include: applying an electrical field, charged moieties near the graphene’s surface, or by chemically modifying the surface, such as chemical binding to the graphene both covalently and non-covalently [Graphene consists of two energy bands, the valence band (VB) and the conductance band (CB), which hold holes and electrons, respectively . The arrolecules , therefovalently .2/Si or epitaxial graphene) is plasma etched away to form a channel [Graphene FETs are generally fabricated using micro fabrication techniques, such as photolithography coupled with metal evaporation or physical vapor deposition (PVD), to pattern and develop the device contacts. The graphene is either then transferred from a copper substrate used for its growth (CVD graphene) or from exfoliated graphene on to a patterned device . Alterna channel . Many G-The channel is then modified to detect target biomarkers by immobilizing bioreceptors onto the graphene channel. This can be done directly (adsorption) or through a linker molecule. The immobilization of a highly specific bioreceptor  to the graphene surface induces chemical specificity towards the target biomarker. Such receptors may include amino acids, enzymes, antibodies, aptamers, or indeed any selective and specific molecule . However2sp carbon atoms makes the graphene surface a potential candidate for covalent bonding [−1 using the diazonium functionalization chemistry [−1 using an epitaxial G-FET functionalized using the APTES method [2sp nature of the carbon atoms. As a result, the 2sp hybridization will be converted to 3sp hybridization [The functionalization of graphene with a linker molecule can be performed through covalent binding to the carbon atoms of the hexagonal matrix or by non-covalent binding to the graphene by electrostatic and/or weak Van der Waals forces . A wide  bonding . Covalen bonding  and hydr bonding  by plasm bonding , such as bonding . Other c bonding  and sila bonding . Tehranihemistry . TeixeirS method . Althougdization , which ddization .2sp nature of the carbon atoms is not affected. Therefore, the electronic and structural properties are not severely disrupted [Non-covalent functionalization is dominated by the physisorption of molecules to the graphene through weak Van de Waals forces . More spisrupted , making isrupted . Chen etisrupted . Furtherisrupted ,38,39,40isrupted , platinuisrupted , palladiisrupted , and zinisrupted . Metal nisrupted . Cai et isrupted . Nucleic acids such as deoxyribonucleic acid (DNA), ribonucleic acid (RNA), and microRNA (miRNA) play a major role in human physiology, and therefore they also play a major role in many diseases. As a result, rapid and highly sensitive detection methods of nucleic acid abnormalities or expression are considered extremely important for disease diagnosis . G-FETs DNA, a double stranded polynucleotide, contains the entire genetic code of an individual, therefore assessing an individual’s genetic makeup can not only aid in the diagnosis of many diseases, but also contains information regarding an individual’s predisposition to genetic diseases and cancers. The DNA nucleotide is made up of a phosphate group, which makes the backbone of the DNA polynucleotide, a sugar (2-deoxyribose), and a nucleobase . These nucleotides arrange in specific sequences through phosphodiester bonding between nucleotides to make up the genome, which stores and transmits genetic information. A complementary strand of DNA then binds via the hydrogen bonding of the nucleobases (A with T and G with C) to make it a double-stranded helix . Since D2 substrate with 45 nm thick Cr/Au contacts by an electrolysis bubbling method. Using a PBASE linker, the 22-mer DNA probe was attached to the graphene surface. It was reported that the Dirac peak of the graphene shifted increasingly at each stage of functionalization , otherwise known as a single nucleotide mutation in the DNA sequence . These mAn important factor in designing a molecular biology test is sensitivity and the linear dynamic range. Both can be influenced by many factors, including but not limited to: graphene quality, a probe’s affinity for the target, the efficiency of hybridization and the surface coverage of the capture probe, and the surface-to-volume ratio. Although graphene inherently has an extremely high surface-to-volume ratio, it can still be a limiting factor when improving the sensitivity of the G-FET. However, it is not impossible to enhance the surface-to-volume ratio further, and, as a result, the sensitivity . Dong et2/Si substrate with Cr/Au/Cr contacts, and applied a polydimethylsiloxane (PDMS) microfluidic to avoid contact interference in the signal. Using the well documented streptavidin-biotin binding mechanism, the 41-mer DNA probe was immobilized upon the graphene surface. A biotinylated bovine serum albumin (BSA) was absorbed onto the channel, and streptavidin was then bound to that biotinylated BSA. The DNA probe  was then introduced, and was able to immobilize upon the channel via binding to one of the three remaining binding sites on the streptavidin. On exposing the eight G-FETs to 100 fM of the target miRNA, a noticeable negative shift was observed due to the electron doping effect of DNA hybridization on the graphene channel. Xu et al. also confirmed the selectivity of their devices by applying a control nucleotide to the sensor. The response seen for the control nucleotide was negligible when compared to the response exhibited by the hybridization event, which occurred between the probe and the target miRNA  probe. PNA is essentially the same as DNA, however due to the exchange of the deoxy-ribose and phosphate backbone for a peptide backbone it is essentially a neutral form of DNA. However, PNA is still able to exhibit an effect on the graphene’s doping due to the electron-rich nucleobase. Therefore, it is still possible to note a shift in the VImmunoassays are biomolecular recognition tests commonly used to determine the presence of biomarkers in a solution and potentially quantify them. More specifically, immunoassays are analytical techniques which rely on biorecognition by antibody-antigen interactions. Therefore, the techniques are based on the specificity and affinity of the antibody for the respective antigen . ImmunosLei and co-workers reported the successful detection of a protein biomarker in whole blood, which is specific to heart failure, using a platinum nanoparticle (PtNP) decorated rGO-FET immunosensor technology. The binding of brain natriuretic peptide (BNP) to anti-BNP was able to be detected through liquid gated measurements at 100 fM. Adding to this, the BNP was able to be distinguished from whole blood proteins, namely, human serum albumin and D-Dimer. Furthermore, BNP was successfully detected in a whole blood sample treated with a microfilter, reported in In 2017, Zhou et al. demonstrated the development of a G-FET for the real-time monitoring of carcinoembryonic antigen (CEA) detection, a biomarker for cancer. Zhou and co-workers reported a detection limit of 100 pg/mL (0.5 pM), far exceeding that of the clinical diagnostics cut-off value. Anti-CEA was immobilized to the G-FET through PBASE, and subsequently the binding of CEA was detected by chronoamperometry. An increase in the drain current was observed, correlating with increasing CEA concentration, as depicted in D), is highly dependent on buffer concentration [D are generally unable to be detected, as the charges within the graphene channel are unaffected [D decreases with increasing buffer concentration [D, and making it difficult to use antibodies as the capture molecule [Even though many immuno-based sensors have been reported in the literature, it is still challenging to reach ultra-high sensitivities because of Debye–Hükel screening . Debye–Hntration . Therefoaffected . As depintration . The Debmolecule .This issue has been addressed by many by only utilizing the antigen binding fragment (Fab) of the antibody. This decreases the distance of the antigen antibody interaction from the surface from approximately 10–15 nm for the whole antibody to approximately 3–5 nm for the Fab, allowing for the use of higher ionic strength buffers ,59. ManyKim et al. reported research addressing this issue. The research directly compared the performance of an aptamer-based G-FET and an antibody-based G-FET for protective antigen (PA), a target analyte for detecting anthrax. A single-stranded DNA aptamer (PA65 5–12) and anti-PA were used. A comparison of the range of detection, sensitivity, and limit of detection proved the aptamer-based sensor to have an overall better performance to the antibody based sensor, as depicted in For over a decade, considerable scientific effort has been directed towards the development of G-FETs for biosensing applications. This review highlights the recent developments in G-FET biosensors, with an emphasis on nucleic acid-based sensors. Label-free G-FETs have shown sensitivities as low as attomolar, far lower than those usually exhibited by other semiconductor technologies or current bioanalytical methods, attesting to G-FET biosensors as a potential platform towards clinical applications. There are, however, challenges faced in the development of G-FET biosensors. One of these limitations is device sensitivity due to the Debye–Hükel phenomenon and limited surface area. These issues were highlighted in The Debye–Hükel phenomenon becomes a hindrance in developing highly sensitive G-FET biosensors, as high ionic strength buffers are needed for the analyte solutions. This decreases the Debye screening length, and as a result decreases the sensitivity of the G-FET to target analytes outside of this length. Therefore, although the field of G-FET technologies is rapidly improving, the development of immunoFETs is hindered by Debye-screening. However, significant R&D efforts have focused on bypassing this issue through the development of nucleic acid-based sensors, aptasensors, and antigen binding fragment (Fab) modified G-FETs. The use of aptamers and Fabs as biorecognition molecules decreases the distance of the interaction from 10–15 nm to 3–5 nm, well within the debye-screening length of 7.4 nm that is seen for 0.01× PBS solution. The development of aptamers and Fabs have led to a biorecognition technology which can replace antibodies and will possibly drive forward the development of immunoFET technologies.The second issue is the surface area of the G-FET sensor. Although graphene has an inherently high surface area, it was reported that this feature could be further improved, and as a result the sensitivity could be increased. This was possible through decorating the G-FET surface with metal nanoparticles, increasing the binding sites for the biorecognition element, and therefore the target analyte.It is clear that graphene has many superior qualities when compared to other semi-conductor technologies. However, the majority of these measured characteristics and aforementioned G-FET sensors have only been achieved using the highest of quality samples within a laboratory setting. To date, most of the work has focused on R&D efforts, as although rapidly improving, these exceptional properties still remain difficult to obtain in a mass-scale manufacturing process . Deokar Furthermore, to develop efficient G-FET biosensors with high accuracy, precision, reproducibility, and lower detection limits, it is vital to improve the biomolecular immobilization strategies. Therefore, more functionalization chemistries need to be identified. The exploration of various bioreceptors, such as aptamers and antibody fragments, would certainly increase their sensitivity. Moreover, the nano-bio interfaces in G-FET sensors should be investigated in more detail. The real-time detection and stability of such sensors also needs to be analyzed in detail to enable the commercialization of G-FET biosensors that exhibit long-term stability and superior performance for clinical practice.


These graphene temperature sensors act as resistance temperature detectors, showing a quadratic dependence of resistance on the temperature in a range between 283 K and 303 K. The observed resistance change of the graphene temperature sensors are explained by the temperature dependent electron mobility relationship (~T−4) and electron-phonon scattering. By analyzing the transient response of the SLG temperature sensors on different substrates, it is found that the graphene sensor on the SiN membrane shows the highest sensitivity due to low thermal mass, while the sensor on SiO2/Si reveals the lowest one. Also, the graphene on the SiN membrane reveals not only the fastest response, but also better mechanical stability compared to the suspended graphene sensor. Therefore, the presented results show that the temperature sensors based on SLG with an extremely low thermal mass can be used in various applications requiring high sensitivity and fast operation.Micro-fabricated single-layer graphenes (SLGs) on a silicon dioxide (SiO The observed superior physical properties of graphene, such as high electron mobility3, mechanical strength5, optical properties7, and thermal conductivity9, have attracted much attention from the research community for a variety of applications12. Although various physical properties of single-layer graphene (SLG) have been measured and predicted14, its thermal properties, such as thermal conductivity, have been continuously investigated to date15. The higher thermal conductivity of graphene in comparison with metals and carbon nanotubes (CNT)16 has led to active research opportunities in thermal management and energy storage applications17. At nanoscale, the performance of electronic devices suffers from elevated temperatures as a result of self-heating, so graphene’s outstanding thermal properties are considered to be suitable for both instrumentation and integrated microelectronic applications18. Recently developed techniques for fabricating complex graphene structures in micro/nano scale21 make graphene a great candidate for temperature sensor applications due to its excellent electrical properties, outstanding mechanical strength, and high thermal conductivity.Graphene is a monolayer of carbon in a honeycomb lattice. Since being isolated from graphite by the micromechanical cleavage method in 2004, the physical properties of graphene have been studied extensively22 and biomedical sensors24. In resistance-based temperature sensors, the initial resistance  and the temperature coefficient of resistance (TCR) are essential parameters for temperature measurement. Commercially available RTDs have a resistance range of 100 Ω to 1000 Ω at 0 °C. For most metals used in RTD applications, the TCR is about 10−3 C−1. A higher TCR value means a higher sensitivity. Thus, lowering the TCR or increasing the thermal mass of a sensor helps to reduce the noise, but lowers the sensitivity.To use graphene as a temperature sensor, the relationship between electrical resistance and temperature needs to be characterized to determine viable applications. A linear relationship between temperature and electrical conductivity can lead to use as a resistive temperature detector (RTD) like metals, while a non-linear relationship can lead it to be used like a thermistor, similar to ceramics or semiconductors. Increasing demands for faster operation speed, improved temperature measurement resolution, and miniaturization capabilities have triggered a search for new materials in temperature sensing applications, such as bolometers18. However, complicated carrier scattering by large densities of defects and residual oxygen contamination in GO and r-GO sheets limits their resistance based applications27. In this paper, we present micro-patterned SLGs placed on silicon dioxide (SiO2)/Si, a silicon nitride (SiN) membrane, and a Si wafer with etched rectangular pits for their use as temperature sensors. After describing the details of the fabrication processes, the device characteristics are investigated by using the 4-wire measurement technique to observe the relationship between electrical resistance and temperature on the SLG temperature sensors on the various substrates. Also, the effects of carrier scattering on the mobility of graphene on different substrates28 are taken into account to explain the observed results.Although SLG has good electrical and thermal properties, no significant temperature sensing application has been studied. Meanwhile, reduced Graphene Oxide (r-GO) and hybrid graphene-GO membranes have been used as temperature sensorset al.29. Graphene layers grown on Cu foils by the CVD method were transferred to a Si substrate covered with a 250 nm thick thermally grown SiO2 layer . Then, the synthesized graphene layers were characterized by Raman spectroscopy31. The measured Raman spectrum clearly shows the G (~1598 cm−1) and 2D (~2712 cm−1) bands with the rarely observed D band near 1350 cm−1, which verifies that the synthesized graphene is a high quality layer. Also, mono-layer graphene was identified by the peak intensity ratio of the 2D band to the G band greater than one, and the full width at half maximum of 2D peak less than 40 cm−1 34.We adapted the process of chemical vapor deposition (CVD) growth of graphene and the transfer method on a substrate from Gunes 2/Si, a SiN membrane, and a Si wafer with etched rectangular pits. After being transferred, the graphene was micro-patterned by a photo-lithography process as shown in Fig. 2 film was used as a substrate. The CVD graphene layer was transferred to the substrate. Then, a thin layer of positive photoresist (PR) was spun, UV exposed, and developed. Then, the exposed graphene was removed by oxygen plasma at 300 W for 10 seconds and the resulting pattern is shown in Fig. The graphene temperature sensors were fabricated on three different surfaces to investigate the scattering effects due to the graphene/surface boundaries on the resistance change as a function of temperature. The synthesized graphene layers were transferred to SiO38. Patterning the graphene device was similar to the graphene on the SiO2/Si. The graphene on the SiN membrane device was constructed with the fabrication process flow as shown in Fig. 2/Si substrate, resulting in a faster measurement. However, the surface roughness is much higher than that of SiO2/Si substrate.To investigate the surface boundary related scattering effects between graphene and the substrate, a graphene device was integrated on a low stress SiN membrane. The SiN membrane was fabricated using an anisotropic wet chemical etching (KOH) as explained previously2/Si substrate was prepared. The pits were fabricated by patterning rectangular boxes (10 × 20 μm2 boxes) using photolithography on the SiO2/Si substrate. The patterned SiO2 was etched with a buffered oxide etchant followed by KOH silicon anisotropic etching. The SLG was transferred on the wafer with etched boxes, and the sensor patterns and electrical contacts were printed over the boxes. Then oxygen plasma at 300 W for 10 seconds was used to etch the exposed graphene as shown in Fig. Surface boundary scattering and defects play a key role in the electrical conductivity of graphene. To reduce the surface effects, a suspended SLG device was prepared. To fabricate the suspended graphene device, rectangular pits on a SiO39. A schematic of a graphene device as a temperature sensor is shown in Fig. μA was used throughout the experiments. The temperature increase due to self-heating at room temperature in this work was less than 0.01 °C. A temperature controlled chamber (water bath) was used to measure the temperature and resistance relationship of the graphene device as shown in Fig. To measure the resistance of the micro-fabricated SLGs on the three different substrates, we used the 4-wire measurement techniqueThe device resistance depends on the conduction electrons. By increasing the chamber temperature the number of electrons will be increased and their mobility will be decreased. A schematic view of the graphene device at low and high temperature is shown in Fig. 2/Si, the SiN membrane, and the suspended substrate are shown in Fig. 2) denoted by the red lines in Fig. 2 ≈ 1. While most metals show linear resistance change behavior as a result of temperature change, thermistors (most semiconductors) show non-linear  resistance changes. In our result, the graphene resistor shows the resistance change is proportional to T2. The electrical conductivity of SLG40 is proportional to the temperature dependent carrier density and mobility of its electrons11: σ = 1/ρ = qnμ, where q is charge, n is the carrier density, and μ is the mobility of the mobile charge. The defects in graphene and the boundaries between the graphene and substrate contribute to carrier scattering, which are directly related to carrier mobility42. These defects can be introduced during the fabrication process, and different boundary conditions can be created by the varying geometry/size and substrate of the device. The significant contribution of interfacial scattering in graphene to electrical properties, like phonon-boundary scattering and graphene contact scattering, have been reported43. For the single layer graphene, it is reported that n is proportional to T2 11. The mobility depends not only on temperature, but also on various scattering mechanisms, such as defects, phonons, surfaces, and edges44. On the scale of our devices , it is a challenge to experimentally identify which scattering mechanism dominates and how it affects electron mobility as a function of temperature. According to previous numerical studies, the electron mobility of SLG considering various scattering mechanisms in a temperature range between 200 K and 350 K was reported to be proportional to T−2 ~ T−4 40, and is limited by electron-phonon scattering in SLG45. The electron mobility in our device is deduced to be proportional to T−4 from the T2 dependent resistance in the range of 283 K to 303 K.The resistance change of the graphene devices in a temperature controlled chamber was measured. The water bath temperature was increased from 10 °C to 30 °C in 5 °C increments. The water bath temperature stayed at each temperature for 2 hours. The 2 hour dwell time at each temperature increment was used for the sensor inside the chamber to reach equilibrium with the water bath temperature. The measured results for the graphene devices on the SiO16 and a very low thermal mass46, the temperature of graphene reaches the bulk silicon temperature quickly. The bulk silicon is in thermal equilibrium with the acrylic device holder and the air inside the chamber  is valid, because the temperature equilibrium characteristics between the apparatus and graphene are the same for each temperature of the water bath. The temperature dependent resistance of graphene is measured from 10 °C to 30 °C because the apparatus starts to physically distort above 35 °C. It was an unexpected experimental fact. The physical distortion of the apparatus applies a mechanical stress on the graphene, causing resistance fluctuations. This response to the mechanical stress shows that graphene is a piezoresistor. The piezoresistive properties of the graphene causes a proportional resistance change due to the applied deformation and strain49.The resistance of graphene continues to increase at a fixed water bath temperature. It takes more than 2 hours for the resistance of the graphene to reach a steady state value in the water bath. This delay in reaching the steady state value may be due to the apparatus of the device holder. The device holder is made of bulky acrylic plates, which the entire device is mounted on. Since the thermal mass of the apparatus is high, it takes a long time  to reach a steady state value with the water bath temperature. The Si substrate is in thermal contact with the acrylic plate and quickly reaches the temperature of the acrylic plate. It takes more than 2 hours for the acrylic plate to reach the water bath temperature. Because graphene has a very high thermal conductivityber Fig. . Althoug2/Si, the SiN membrane, and the suspended architecture are estimated to be 1.25, 2.15, and 1.90, respectively. So, the graphene on the SiN shows the highest normalized resistance sensitivity, while the graphene on SiO2/Si is the lowest one.In addition, in Fig. 50, the temperature response of the graphene follows the response of the SiN membrane. The response of the graphene on the SiN membrane is slower than that of one without the PDMS due to the PDMS thermal mass. The metal sensor made of a 100 nm-thick nickel film on the SiN membrane shows the third fastest response. Compared to graphene, the metal layer has a higher thermal mass, causing a slower response than the graphene layer. The suspended graphene sensor shows the second slowest temperature response. The high thermal conductivity of graphene is expected to lead to a fast response to environmental temperature changes. However, the graphene sensor is suspended across the Si substrate with a suspended length of 20 μm equilibrates with the substrate, causing the slower response. This is because the substrate was mounted on an acrylic plate, which has a higher thermal mass. The slowest response is shown for the graphene sensor on the SiO2/Si substrate mounted on an acrylic plate due to having the highest thermal mass among the five configurations. The graphene temperature sensor on the SiN membrane has not only the fastest response, but also better mechanical stability compared to the suspended graphene sensor. Therefore, the optimal configuration of a graphene based temperature sensor would be the graphene sensor on a SiN membrane.Furthermore, the effect of the substrate on the device temperature transient response for five different configurations have been investigated as shown in Fig. 51 as shown in Fig. sccm, was continuously flown through a chamber (400 cm3), where the sensor is placed. Figure 52. Besides the doping effect, the resistance of the graphene sensor increases at the elevated temperatures as shown in Fig. The graphene temperature sensor can be affected by surrounding environments. For example, the humidity modulates the resistance of the graphene sensorMicro-patterned SLG devices were fabricated and characterized as temperature sensors, showing the characteristics of temperature response between those of metals and thermistors. The quadratic dependence of resistance on the temperature for the fabricated graphene sensors was analyzed using the temperature-dependent carrier density and electron mobility model. The graphene sensor placed on the SiN membrane reveals not only the fastest response and the highest sensitivity due to the low thermal mass, but also better mechanical stability compared to the suspended graphene sensor. As a result, the suggested SLG on a SiN membrane can be an efficient temperature sensor for use in various fields requiring highly sensitive and fast operation.μm-thick copper foil  was loaded in the CVD reactor and pumped to the base vacuum pressure (<10−4 Torr). The copper foil was vertically placed on a substrate holder in the central isothermal growth zone of the reactor during the growth process. The temperature of the chamber was ramped up to 1060 °C with a mixture of Ar (2000 sccm) and H2 (30 sccm) at the processing pressure of 470 Torr. The copper foil was typically annealed for 2 hours. The furnace temperature was then decreased to the process temperature of 1020 °C with pure 30 sccm H2 gas only at 570 mTorr. When the temperature reached 1020 °C, graphene layers started to grow on the copper foil when a methane/hydrogen gas mixture (CH4 = 40 sccm and H2 = 100 sccm) and 2000 sccm Ar as a carrier gas were introduced to the reaction chamber at 600 mTorr for 30 min. The reaction chamber was then cooled down to room temperature with an average rate of 14 °C/min under the same Ar/H2 gas flow rates without methane.The CVD reactor we used is a horizontal quartz tube, which is 2400 mm long and 152 mm in diameter. This quartz tube was placed in a 1500 mm long six-zone furnace. A 25 μm-thick PMMA  was spin-coated on the as-synthesized graphene on copper foil at 3000 rpm for 100 seconds. The PMMA was baked in an oven at 120 °C for 10 minutes. Because the CVD process grew graphene layers on both sides of the copper foil, graphene layers the other side (no PMMA) of the copper foil were removed by oxygen plasma (60 W power for 10 minutes). The copper foil was then removed by floating the sample on a copper etchant  for 40~60 min. To rinse the graphene after copper etching, the PMMA/graphene was removed from the etchant and placed in two subsequent DI water baths for 20 min each. After the DI water rinsing, the PMMA/graphene layer was transferred onto a SiO2 (300 nm)/Si (100) wafer. Then, the PMMA was removed by acetone in an ultrasonic bath for 20 min, leaving the SLG on the SiO2/Si wafer. The single layer graphene on the SiO2/Si wafer was then rinsed in a 30% HCl solution at 60 °C for 30 min to remove residual Fe+3 ions. As a result, the high-quality graphene layer with a low defect density was prepared on the SiO2/Si substrate on a large scale  membrane, and a silicon wafer with etched rectangular pits were patterned by a photo-lithography process. During the lithography process, the photoresist (PR) remaining on the graphene was removed by acetone after patterning the graphene. Since the surface and parts of the graphene were damaged during the removal of the PR, the PR on patterned graphene was not removed. Then, this remaining PR was used to support the suspended graphene over the pits  with a 100X lens  and a 532 nm laser (~1 mW) polarized by a GX-AN360 (Olympus) filter. Each spectrum was obtained by 10 acquisitions in 10 s of accumulation time. Three to six analyses were performed at various places on each sample.Graphene layers grown on Cu foil by the CVD method were transferred on the SiOElectrical contacts to external electrical measurement units were made using silver paint  and 40 AWG copper wire  on the graphene contact pads in a wire bonding fashion. It should be noted that typical silver epoxy  may dissolve or make a poor electrical contact with the graphene based on the observations during the experiments. Despite this occasional malfunction, the 4-wire measurement eliminated any lead resistance (graphene traces and conductive epoxy) from contributing to the temperature sensor resistance.