In this review we highlight recent theoretical and experimental work on sublattice asymmetric doping of impurities in graphene, with a focus on substitutional nitrogen dopants. It is well known that one current limitation of graphene in regards to its use in electronics is that in its ordinary state it exhibits no band gap. By doping one of its two sublattices preferentially it is possible to not only open such a gap, which can furthermore be tuned through control of the dopant concentration, but in theory produce quasi-ballistic transport of electrons in the undoped sublattice, both important qualities for any graphene device to be used competetively in future technology. We outline current experimental techniques for synthesis of such graphene monolayers and detail theoretical efforts to explain the mechanisms responsible for the effect, before suggesting future research directions in this nascent field. With its excellent transport properties and low dimensionality, graphene, an atomically thin layer of Carbon atoms bonded together in a hexagonal lattice, initially seems a strong candidate for use in many future commercial applications such as ultra high-speed transistors, integrated circuits and other novel devices –3. One o4–107 and a band gap of at least 340 meV whilst maintaining high carrier mobility [Although several methods exist to induce a band gap, for example 1D quantum confinement by construction of graphene nanoribbons (GNRs) , stackinmobility ,13–14.Alteration of the crystal structure through the introduction of foreign dopants is one of the more realistic avenues of approach in realising this goal. Atomic dopants like boron (B) or nitrogen (N) are a similar size to carbon and can be introduced easily in a variety of graphene growth processes, typically replacing carbon sites and forming substitutional impurities in the lattice, positively (p-) and negatively (n-) doping the system for B and N dopants respectively . Early tWhilst these findings are certainly interesting, their scalability, and hence commercial application, is prohibited by the standard of precision that must be met in order to produce such materials. Circumventing these problems using nitrogen doped graphene has only come about relatively recently which we detail in the following section.3 as a precursor, arc discharge [Exploiting the effects of nitrogen dopants on the transport properties of graphene has been an interesting experimental research topic for the last 5 years , wherebyischarge , embeddeischarge , ion impischarge –26, ammoischarge  or nitroischarge –29 treatischarge  and withischarge . Althougischarge  and singischarge . Using nischarge  and by iischarge . Boron discharge –35. Thisischarge –37, whic3) naturally incorporates nitrogen atoms as substitutional so-called ’graphitic’ dopants , followed by a short investigation on the transport properties of the resulting graphene. Their experimental observation of same sublattice segregation, at least on local scales, was noted as a curiosity but was not discussed in depth. A key finding by the researchers was that by varying the ammonia precursor concentration they could adjust the resulting embedded dopant concentration. Further theoretical work confirmed that a tunable band gap would be obtainable using this method , and alo2AA pairs [2AA to single N increasing with reaction time. The samples had a typical concentration of around 0.25% nitrogen dopants.Shortly after this work a more focussed investigation was undertaken by Lv et al. . They weAA pairs   substrate and the boron impurity, in contrast to a very weak interaction with the substrate for nitrogen impurities [More recently the addition of boron dopants into the lattice and their effects have been studied  using hipurities .5H5N) precursor for the nitrogen and graphene instead of the conventional ammonia/methane mix. The most recent and thorough study of asymmetric nitrogen dopants in graphene is by Zabet-Khosousi et al.  who agaiThe common elements of all the aforementioned experimental reports are that they all use a Cu(111) substrate, all have reaction times exceeding 10 min in a temperature range of 800–900 °C, and all have used either ammonia or pyridine precursors to achieve concentrations of up to 0.3%. A review of other methods for N-doped graphene synthesis finds no mention of sublattice asymmetry –30, it iIt is clear that any degree of asymmetry between the two equivalent sublattices is the result of a symmetry breaking operation. Current theoretical attempts to explain the sublattice asymmetry in the nitrogen doping seen in the experiments discussed in the previous section suggest that the effect comes from either the energetically preferable positioning of nitrogen on the graphene edge during the growth process –42, wherThe edge growth model suggests that during the growth phase the most energetically favourable position for a nitrogen dopant being incorporated into a graphene edge would be that which leads to a same sublattice configuration for all impurities in a domain. Through density functional theory (DFT) calculations involving a graphene nanoribbon on a Cu(111) substrate, aiming to reproduce experimental conditions, a thorough investigation into the energetic favourable position of single graphitic nitrogens in the GNR was undertaken and the energetic difference between placing the nitrogen at one edge site over another on the opposite sublattice was found to be a substantial 1.3 eV. One drawback of this method is that one would expect therefore that the clearly defined segregation domains seen experimentally (see 2AB. This contradicts the experimental reports of Lv et al. [2AA defects in their samples. A simplistic tight binding approach predicts that two identical impurities in close proximity to one another would indeed have an energetic minimum when both occupy the same sublattice [2AB′ (see 2AA. This appears to be in disagreement with experiments where N2AA is more commonly found than N2AB′. As a final note their calculations have also shown that two N2AA pairs have a lower energy when they share the same sublattice, however further studies have shown that the overall energy change resulting from an N2AA pair in the sheet is very high [2AA in nitrogen ion implanted graphene [In-depth DFT calculations by Hou et al.  found thv et al.  who founblattice , however2AB′ see , approxiery high . It is pgraphene  indicateThe earliest attempts to study nitrogen dopants and their effect on the graphene electronic properties were purely theoretical. Beginning with impurity superlattices, this research preceded the experimental realistation of nitrogen doped graphene. By introducing a controlled periodic arrangement of boron and nitrogen impurities a band gap was seen to open , and altEven with a 4:1 doping ratio between sublattices, the band gap, although smaller, was shown to still exist. This is promising for scaleability where perfect asymmetric doping may not always be realizable. Beyond the realization of quasi-ballistic electron transport, sublattice segregated systems can also be used to induce magnetism ,48–50 anMuch work has been done studying how the placement of dopants affects the properties of nanoribbons. DFT approaches, using a periodic system of dopants –54, and It should also be noted that that symmetry breaking in nanoribbons occurs via edge effects and also results in a favourable sublattice , howeverAt the time of writing, the synthesis of sublattice asymmetric graphene is only just now becoming practical. There are still many unanswered questions and the most important ones we outline in this section.The natural question to ask is if this asymmetry is particular to nitrogen only, or if it can be found with other dopants. Theoretical findings in the past have shown that such an effect can be expected with a dilute concentration of certain adsorbates , and indThe experimental realisation of spin-polarized transport should also be pursued, and could spark additional interest in this research area beyond quasi-ballistic transport. Investigation of the effects of strain on such a system is difficult due to the technicalities of the CVD method, but could be explored using adsorbates instead of substitutions or by incorporation of the strain in to the nitrogen ion bombardement and annealing procedure discussed earlier. Another open question is if a critical concentration of dopants exists, as mentioned in the theory section, which would limit the available bandgap below the threshold needed for future use in GFET devices. Currently all experimental reports on sublattice asymmetry have very low concentrations of dopants around 0.3%, so it should be feasible to test the existence of a critical concentration of using available methods . ConsequThis paper reviews the current state of experimental and theoretical research in sublattice asymmetric nitrogen doped graphene. Not only are such systems now able to be synthesised in the lab, we have seen that this area shows promise attaining graphene-based FET devices due to the opening of a bandgap whilst maintaining the excellent transport properties of graphene, something which is not realisable in graphene with no sublattice imbalance in dopant distribution. While there are still many open questions in the field these should be answerable within the scope of current techniques.


Previous studies have presented algorithms for detection of turns during gait using wearable sensors, but those algorithms were not built for real-time use. This paper therefore investigates the optimal approach for real-time detection of planned turns during gait using wearable inertial measurement units. Several different sensor positions  and three different detection criteria  are compared with regard to their ability to correctly detect turn onset. Furthermore, the different sensor positions are compared with regard to their ability to predict the turn direction and amplitude. The evaluation was performed on ten healthy subjects who performed left/right turns at three amplitudes . Results showed that turn onset can be most accurately detected with sensors on the back and using a combination of orientation and angular velocity. The same setup also gives the best prediction of turn direction and amplitude. Preliminary measurements with a single amputee were also performed and highlighted important differences such as slower turning that need to be taken into account. For example, a powered prosthesis can provide different types of support depending on whether the user wishes to walk, stand in place or sit down . While tMost gait analysis studies with wearable sensors have focused on steady-state walking, where they extract parameters such as stride length  and deteMost automated gait analysis algorithms treat gait as taking place only in the sagittal plane of the body, allowing considerably simplified calculations ,12. HoweNumerous personal navigation algorithms have been developed for wearable sensors to track and reconstruct walking trajectories over longer distances ,17. Whilet al.  s,-Percentage of correctly classified amplitudes at T = ONSETT +  s.Direction and amplitude classification were evaluated as:These were calculated at different times since we assume that the turn direction and amplitude are easier to identify later in the turn. They were calculated only for trials where a turn is detected correctly (within 500 ms of the reference).2.6.Since we lack access to amputee subjects, the pilot test with the amputee was performed at a different location by the same experimenters on the same day as a larger set of measurements for an unrelated gait analysis study. The amputee wore IMUs on the lower back, thighs, shanks and feet like the unimpaired subjects, but upper back and head IMUs were omitted for logistical reasons. Furthermore, due to time constraints, only 12 trials were performed: two for each turn direction (left/right) and amplitude (22/45/90 degrees).Since there were not enough trials to perform within-subject crossvalidation with the amputee, only a form of subject-independent crossvalidation was performed: the onset detection and direction/amplitude classification algorithms were trained using data from all healthy subjects and tested on the 12 amputee trials. Results are given in Section 3.3.3.The total duration of one trial across all ten unimpaired subjects was 16.4 s ± 2.2 s (mean ± standard deviation). Subjects began walking 8.3 s ± 2.3 s after the start of the trial. In trials where a turn occurred, turn onset was 10.2 s ± 2.3 s after the start of the trial. Examples of the upper back gyroscope signal and angle are shown for unimpaired subjects in 3.1.In this section, we present onset detection results for the three different criteria: orientation threshold only , angularComparing the results in gyr_thresh and angle_thresh to detect onset, the optimal subject-independent thresholds are gyr_thresh = 58°/s and angle_thresh = 23°. In the within-subject case, the optimal gyr_thresh varies (among subjects) from 25°/s to 80°/s while optimal angle_thresh varies from 22 to 30°. Similar values (subject-independent optimum: gyr_thresh = 56°/s and angle_thresh = 23°) were obtained for the lower back IMU. The intersubject variation in optimal gyr_thresh is likely due to subjects turning at different speeds.If we use the upper back IMU with both gyr_thresh and angle_thresh to detect onset, the majority of detection errors in within-subject crossvalidation are due to 22-degree turns: out of all premature/late detections and false negatives, 72% occur with 22-degree turns, 20% with 45-degree turns, and only 8% with 90-degree turns. Interestingly, this is not the case in subject-independent crossvalidation: there, out of all premature/late detections and false negatives, 31% occur with 22-degree turns, 39% with 45-degree turns and 30% with 90-degree turns.Furthermore, if we use the upper back IMU with both For the combination of both thresholds (orientation and angular velocity), we additionally evaluated the onset detection for the special case where only larger turns are considered . It can 3.2.As mentioned, turn direction and amplitude classification was evaluated only for trials where turn onset was correctly detected by the IMU. Classification accuracy is shown in In general, the head IMU provides the most reliable direction and amplitude information in within-subject crossvalidation, followed by the two IMUs on the back. In subject-independent crossvalidation, the IMUs on the back are the most accurate. Though not reported in detail, the majority of misclassifications occur with 22- and 45-degree turns. For example, with the upper back IMU, 90-degree turns represent less than 20% of all misclassifications at any given time for both crossvalidation types. At 0.3 s since detected turn onset (or later), 90-degree turns represent less than 10% of all misclassifications for both crossvalidation types.vs. both thresholds), and we have only reported direction and amplitude classification results for the best case when both onset thresholds are used.Care should be taken when comparing turn direction and amplitude classification results from the different IMUs. Since classification is performed only for trials where the turn onset is detected correctly, it is not possible to directly compare e.g., upper back results (where over 85% of turn onsets are correctly detected) with foot results (where less than 75% of onsets are correctly detected). It is therefore also difficult to compare results between different onset detection criteria  However, turn amplitude classification was largely unsuccessful: at the time of detected turn onset, amplitude was correctly classified in 4 of 9 trials using the lower back IMU and 3 of 7 trials using the thigh IMU. 0.5 s after detected turn onset, amplitude was correctly classified in 5 of 9 trials using the lower back IMU and 4 of 7 trials using the thigh IMU.4.4.1.Results from unimpaired subjects indicate that, whatever the onset detection criterion, the best results can be obtained using an IMU placed on the upper or lower back. While there are only small and inconsistent differences between the two IMUs on the back, the IMUs on the legs consistently produce worse onset detection results as well as lower percentages of correctly classified turn directions and amplitudes. The cause for this is not clear, but we believe that it is due to two reasons. The first reason is the top-down turning strategy, where the upper body generally turns earlier than the lower body ,22. The The head IMU is a special case. The majority of subjects look at the endpoint for the current trial even before starting to walk, and vary between looking straight ahead or looking at the endpoint. Thus, while information about the walking direction is visible in the signals from the head IMU, it cannot be used to predict when the turn itself will occur.We can conclude that, if we wish to detect turn onset rapidly with a single IMU, it should be placed on the trunk rather than the legs. This importance of the upper body during gait is not new and has been previously emphasized in the context of lower limb exoskeletons ,23, but 4.2.For unimpaired subjects, the orientation threshold can be used to correctly detect about 75% of turns using the upper and lower back IMUs in within-subject crossvalidation. The angular velocity threshold correctly detects slightly over 80% of turns using the upper and lower back IMUs in within-subject crossvalidation, but also produces more false positives. Combining both thresholds for onset detection produces the best results, with the highest percentage of correct detections and a low percentage of false positives . DependiThe amputee, who turns more slowly, exhibits lower angular velocity peaks compared to healthy subjects. This suggests that the angular velocity threshold may be less useful in both amputees and in elderly unimpaired subjects who would also turn more slowly than young subjects. However, the combination of orientation and angular velocity thresholds on the lower back was still able to achieve a reasonable percentage of correctly detected onsets.It should be noted that, although combining the two thresholds allows turn onset to be detected accurately with respect to an optical reference, this is only important if we are interested in real-time detection where smaller detection delays give an assistive device more time to react. For annotation of offline data, an orientation threshold is sufficient, as has been shown in previous work ,19. Neit4.3.The best results were obtained in within-subject crossvalidation, where the algorithms are trained individually for each subject. This implies that, for any online application, the algorithms should also first be trained individually for each subject. Depending on how robust we wish the trained algorithms to be, this training process may be time-consuming as trials of different speeds and turn amplitudes are collected in different conditions. Our own measurement protocol required over 30 minutes for each subject and was conducted at a single walking speed.et al. [The main foreseen application of the algorithm is in assistive devices such as powered prostheses. Such a device would not be used by many people, but even training for one person would be time-consuming. The best approach may be a combination of subject-independent and subject-specific training. For example, the hand prosthesis control approach of Tommasi et al.  starts w4.4.The cost function used to train the onset detection algorithm (Section 2.4.1) represents a weakness of the study, as it is somewhat arbitrary. An intuitive alternative would have been to replace it with a more complex way of finding a threshold. We used more complex methods for gait event detection in our previous studies ,11 but wThe manual approach for onset detection used by the human experts may also bias the algorithm’s results. For example, since the Optotrak markers are placed on the head and trunk rather than the legs, the expert-defined reference onset is more likely to match the lower and upper back IMUs since they are also placed on the legs. We believe that the delays in turn onset between the trunk and legs are much smaller than the 500-ms interval for correct detection, and that this issue therefore did not have a major effect, but it should nonetheless be mentioned.Within the cost function, some parameters have been chosen ad-hoc based on our own experiences and previous studies. For example, the 500-ms criterion for error computation was chosen based on two things. First, previous studies in arm prosthetics have shown that delays over 300 ms are unacceptable for real-time control [4.5.The main weakness of the presented approach is the limited evaluation, which was done mostly with relatively young, healthy subjects and only a single amputee. Preliminary results from the amputee suggest that turning behavior is not entirely dissimilar in amputees compared to healthy subjects, and onset detection rules can be transferred from healthy subjects to amputees to some degree. However, the amputee does turn more slowly, with lower angular velocity peaks. This suggests that an angular-velocity-based threshold for onset detection may be less useful for amputees and elderly subjects. The slower turning speed may also be the reason why turn amplitude classification was not successful in the amputee.Furthermore, in a few amputee trials, the turn onset is visible essentially simultaneously for all IMUs see . These tIn general, elderly subjects are known to exhibit different turning behavior ,22. Addi4.6.Though our algorithm has not been tested with an assistive device, we can briefly describe the expected application. While the wearer walks with the assistive device (powered prosthesis or orthosis), the algorithm constantly checks whether a turn onset is occurring. Once the onset is detected, the algorithm should immediately notify the device that a turn is occurring, causing it to switch from assisting forward gait to ensuring stability during the turn, similarly to a stumble detection algorithm . The dev5.This paper builds on previous turn detection algorithms by presenting an optimal setup for real-time turn onset detection during gait using IMUs. Based on our measurements, two conclusions should be drawn. First, IMUs should be placed on the trunk (upper or lower back) rather than the legs for most accurate turn onset detection. Second, a combination of thresholds on orientation and angular velocity provides better results than a single threshold (orientation or angular velocity). Once turn onset has been detected, turn direction can also be easily detected from the IMUs on the back, though amplitude is more difficult to detect. Subject-specific detection thresholds provide better results, though they may be time-consuming to train.The turn detection algorithm is foreseen for use with assistive devices that need to react to a turn as quickly as possible. Using our cost function, the detection thresholds can be adapted so as to, for example, minimize false positives or false negatives. However, our preliminary test with the amputee highlighted important differences between unimpaired and impaired subjects, such as the slower turning speed. Therefore, further evaluations with target populations and with more difficult situations  are required to determine the extent to which our findings can be generalized.


The timed up and go test (TUG) is a functional test which is increasingly used to evaluate patients with stroke. The outcome measured is usually global TUG performance-time. Assessment of spatiotemporal and kinematic parameters during the Oriented gait and Turn sub-tasks of the TUG would provide a better understanding of the mechanisms underlying patients’ performance and therefore may help to guide rehabilitation. The aim of this study was thus to determine the spatiotemporal and kinematic parameters which were most related to the walking and turning sub-tasks of TUG performance in stroke patients.29 stroke patients carried out the TUG test which was recorded using an optoelectronic system in two conditions: spontaneous and standardized condition (standardized foot position and instructed to turn towards the paretic side). They also underwent a clinical assessment. Stepwise regression was used to determine the parameters most related to Oriented gait and Turn sub-tasks. Relationships between explanatory parameters of Oriented gait and Turn performance and clinical scales were evaluated using Spearman correlations.Step length and cadence explained 82% to 95% of the variance for the walking sub-tasks in both conditions. Percentage single support phase and contralateral swing phase (depending on the condition) respectively explained 27% and 56% of the variance during the turning sub-task in the spontaneous and standardized conditions.Step length, cadence, percentage of paretic single support phase and non-paretic swing phase, as well as dynamic stability were the main parameters related to TUG performance and they should be targeted in rehabilitation. Patients with stroke-related hemiparesis frequently have impaired balance and gait, limiting daily life activities. The improvement of locomotor skills is therefore a major aim of stroke rehabilitation  and an aMotion analysis would be a pertinent method to investigate biomechanical aspects of the TUG. The use of instrumental biomechanical tools to assess functional tasks has increased over the past few years. Galli et al 2008) and Lecours et al (2008) both quantified kinematics and kinetics during sit to stand in subjects with stroke and healthy subjects , 7. Dion and LecoThree-dimensional analysis using an optoelectronic system is the current gold standard for the biomechanical assessment of patients with gait abnormalities . This meThe aim of this study was thus to determine which spatio-temporal and/or kinematic parameters would be the most related to performance in Oriented gait and Turn sub-tasks of the TUG test (time to perform the sub-task) in stroke patients. We hypothesized that the percentage of single support phase and peak hip extension on the paretic side would be particularly related to the performance of Oriented gait and Turn sub-tasks of the TUG. The percentage of single support phase during gait has been shown to predict the time to perform the entire TUG test and peak hip extension has been shown to be associated with gait speed , 15.Twenty nine participants with chronic hemiparesis were included  . The inc3D-TUG analysis was carried out using an optoelectronic motion capture system . Markers were fixed to specific bony landmarks on both sides of the body according to the Helen Hayes marker set , 17: theIt has been shown that seat height, foot position and turning direction influence the sit to stand movements and TUG performance in healthy and stroke subjects , 22, 23.Marker trajectories were recorded using 8 infrared cameras and filtered using a low-pass Butterworth filter with a cut off frequency of 6 Hz . AnatomiThe data were then exported to Matlab  for calculation of the biomechanical parameters in each sub-task.Time taken to perform each sub-task, which corresponded to TUG performance.Spatiotemporal parameters: cadence, width, and step length and percentage of single support phase (%SSP) and swing phase (%SP) for each limb.Kinematic parameters: peak flexion and extension of the hip, knee and ankle on the paretic and non-paretic sides. For the ankle, maximal dorsiflexion was also calculated during swing phase.The parameters analyzed were:Spasticity of the whole quadriceps, rectus femoris (one head of the quadriceps), hamstring and triceps surae was evaluated with the Modified Ashworth Scale (MAS) . Strengt0+ b1X1+ b2X2+….+ bpXp where Y is the explanatory value, X1 through Xp are p distinct explanatory variables, b0 is the value of Y when all the independent variables (X1 through Xp) are equal to zero and b1 to bp are the estimated regression coefficients. Each regression coefficient represents the change in Y relative to a one unit change in the respective independent variable.Descriptive statistics including means and standard deviations were calculated for each parameter and Oriented gait  and Turn in both conditions (Spont and Stand). To identify the spatiotemporal and kinematic parameters which were the most related to Oriented gait (Go and Return) and Turn performance, a stepwise multiple regression analysis with forward selection was used. The number of variables included in the stepwise analysis has to be small compared to the number of subjects . FirstlyA Spearman’s test was then used to evaluate correlations between variables found to explain TUG performance from the stepwise analysis and clinical tests since clinical data were not continuous (level of significance p<0.05).Results of the Oriented gait (Go and Return) and Turn performance and spatiotemporal and kinematic parameters for each sub-task and both conditions (Spont and Stand) are presented in In Spont: 4.83(1.18)s for Go, 2.98 (0.73)s for Turn and 4.23(1.02)s for Return;In Stand: 4.56(1.01)s for Go, 3.16(0.84)s for Turn and 3.81(0.91)s for Return.In Spont, sixteen participants turned towards the paretic side, 10 towards the non-paretic side and 3 changed turn direction within the 3 trials.Median summed spasticity score was 4±3.6, median summed MRC score was 23±5.7, median pressure score on the sole of the foot was 1±0.5 and median proprioception score for the toe was 2±1.1 (both assessed with Nottingham Sensory Assessment). Eighteen subjects had claw toe in standing. Mean BBS score was 50.5±2.3, mean ABC score was 76.3±12.9. The median rate of falls was 1±0.7 and median fear of falling score was 2±3.2.Go: step length, %SP and %SSP on both sides and cadence and peak hip flexion on the paretic side were significantly negatively correlated with Go performance.Turn: paretic step length and %SP and non-paretic %SSP were significantly negatively correlated with Turn performance.Return: step length and %SSP on both limbs, non-paretic %SP and cadence were significantly negatively correlated with Return performance.Go: step length, %SP and %SSP on both sides and cadence were significantly negatively correlated with Go performance.Turn: %SP and %SSP on both sides and paretic step length and paretic peak knee extension were significantly negatively correlated with Turn performance.Return: step length, %SP and %SSP on both sides and cadence were significantly negatively correlated with Return performance.Step length on both sides and cadence were selected for Go, explaining 93% of the variance of Go performance.For Turn, non-paretic %SSPwas the only variable selected, explaining 27% of the variance of Turn performance.Turn performance = 6.8 − 0.08 non - paretic %SSPFor Return, step length on both sides and cadence were selected, explaining 82% of the variance of Return performance.➢ For Go, step length on both sides and cadence were selected, explaining 95% of the variance of Go performance.For Turn, non-paretic %SPand paretic %SSP were selected, explaining 56% of the variance of Turn performance.For Return, non-paretic %SP, cadence and step length on both sides were selected, explaining 87% of the variance of Return performance.Results of the stepwise analysis for both conditions are summarized in The BBS score was positively related to most parameters. MRC, fall frequency, fear of falling and MAS were only related to a few parameters. No correlations were found between the presence of claw toe, foot sole pressure score, toe proprioception score and ABC score and any biomechanical parameter.To the best of our knowledge, the present study is the first to use 3D motion analysis to investigate spatiotemporal and kinematic parameters during Oriented gait and Turn sub-tasks of the TUG test in order to provide a deeper understanding of locomotor control in patients with stroke. The aim of this study was to determine the spatio-temporal and kinematic parameters which relate to performance in Oriented gait and Turn sub-tasks of the TUG in stroke patients. The results showed that in the spontaneous condition, step length on both sides and cadence best explained Go and Return performance, whereas percentage non-paretic SSP best explained Turn. In the standardized condition, the same parameters were selected in the stepwise analysis for Go and Return, and in addition, percentage non-paretic SP was selected in Turn and Return and percentage paretic SSP in Turn. Our hypothesis is partly confirmed since the percentage of single support phase was related to timed Turn performance but peak hip extension was not.It is not surprising that step length and cadence explained performance in the walking sub-tasks since gait speed is the product of step length and cadence. Correlations have previously been found between total TUG time and gait speed . ImproveNone of the kinematic parameters studied explained Oriented gait and Turn performance. This corroborates with a previous study which highlighted that kinematic parameters during conventional gait analysis were not predictive of the time to perform the entire TUG test . Since iSurprisingly, no correlations were found between MRC scores and the biomechanical parameters which were related to the Go and Return sub-tasks. Previous studies have shown that the best predictors of gait performance are strength of the paretic lower limb and balance in stroke patients . AnotherPercentage SSP appears to play an important role in the Turn sub-task although the limb (paretic or non-paretic) differed according to the condition. This corroboratesa previous study in our group showing that paretic %SSP assessed during conventional gait analysis is predictive of total TUG performance time in stroke patients . In stroTo summarize, these results indicate that the walking sub-tasks of the TUG test which require a forward progression of the body are mainly affected by step length and cadence, while the turning sub-task of the TUG requires balance control which is related to the percentage of the gait cycle spent in stance phase. However, the percentage variance explained was high for the Go and Return sub-tasks (between 82% and 95%) and moderate for the Turn (27% and 56%) in both conditions. Both conditions (Spont and Stand) lead to the same explanatory parameters for walking sub-tasks (step length and cadence). In contrast, the Stand condition better explained the variance for the Turn sub-task, we therefore suggest that the standardized condition is more pertinent for the biomechanical assessment of Oriented gait and Turn sub-tasks of TUG performance. Confidence in carrying out activities (ABC score) was surprisingly not related to any of the biomechanical explanatory parameters. Oriented gait and Turn sub-tasks of TUG test appears thus more related to a global fear of falling than confidence to carry out specific activities.The sample of participants in the present study was a little younger (54.2±12.2 years) than other studies in the literature. However, it is unlikely that this would have influenced the results since Oriented gait and Turn sub-tasks of TUG performance was similar to that reported by Faria et al who found a time of 10.36s for the walking sub-tasks (summed) and 3.18s for the turning sub-task in patients with chronic stroke (mean age 59.12±2.28y) . SimilarThe differences found between the Spont and Stand conditions may be due to the fact that the Spont condition was always performed first. However, for the spontaneous condition to reflect spontaneous performance, it was essential for it to be carried out first. A similar methodology was used in another study .This study investigated spatiotemporal and kinematic parameters in Oriented gait and Turn sub-tasks of the TUG test in stroke patients. The results showed that step length and cadence explained most of the variance in the performance of the walking sub-tasks and, %SSP and %SP explained the turning sub-task. Balance capacity (assessed with BBS) and fear of falling were associated with the biomechanical parameters which explained performance in both the walking and the turning sub-tasks whereas spasticity, strength, sensation and proprioception were not, or only very slightly, related. It can thus be concluded that dynamic stability is the main capacity required to perform the walking and turning sub-tasks of the TUG. The results of the Spont and Stand conditions differed slightly, probably due to the different directions of the turn. More variance was explained in the standardized condition and therefore we suggest that this condition should be used to evaluate Oriented gait and Turn sub-tasks of TUG performance. This study demonstrated that biomechanical analysis of the Oriented gait and Turn sub-tasks of the TUG is useful to increase understanding of gait abnormalities. This is relevant for rehabilitation since the tasks evaluated by the TUG are highly functional and are carried out frequently throughout the day, however are rarely assessed using accurate tools. This analysis assesses balance capacity during gait, either for monitoring purposes or to evaluate the effects of treatment . Moreover, the results of this assessment can be used to optimize rehabilitation, for example, to improve performance during the gait sub-tasks, rehabilitation should focus on increasing cadence and step length, whereas to improve the performance on the turning sub-task, balance capacity and particularly single support phase on the paretic side should be specifically trained.


In this perspective article, we consider the relationship between experience sharing and turn-taking. There is much evidence suggesting that human social interaction is permeated by two temporal organizations: (1) the sequential framework of turn-taking and (2) the concurrent framework of emotional reciprocity. From this perspective, we introduce two alternative hypotheses about how the relationship between experience sharing and turn-taking could be viewed. According to the first hypothesis, the home environment of experience sharing is in the concurrent framework of emotional reciprocity, while the motivation to share experiences is in tension with the sequential framework of turn-taking. According to the second hypothesis, people’s inclination to coordinate their actions in terms of turn-taking is motivated precisely by their propensity to share experiences. We consider theoretical and empirical ideas in favor of both of these hypotheses and discuss their implications for future research. In recent years, there has been an increasing number of conversation analytic studies explicating the social organization of, and the highly ordered interactional tasks performed by, emotional expressions in social interaction e.g., . This pesequential framework of turn-taking. It denotes not only the temporal but also the conditional relationship between participants’ interactional moves.Many naturally occurring interactions call for individuals to coordinate their actions in terms of turn-taking. This happens especially in the context of language use: the principle of one participant talking at a time  allows hconcurrent framework of emotional reciprocity. The literature on “emotional contagion” suggests that humans have an automatic tendency to mimick other people’s non-verbal emotional expressions, which affects the emotional experience of the mimicking person  telling lines 1–6) both participants are looking down with straight faces (Frame 1). At the end of the telling, however, they establish mutual gaze and the teller (B) adopts a smiling face (Frame 2). After a gap (line 7), the recipient (A) reciprocates the smile and raises her brows (Frame 3), simultaneously producing an animated verbal response of “ritualized disbelief” , they ma–6 both pThe idea of experience sharing being in tension with the sequential temporality of turn-taking reverberates with certain recent suggestions presented in the conversation analytic literature: The points detailed above suggest that the home environment for experience sharing might be in the concurrent framework of emotional reciprocity, while experience sharing  may call for the participants to depart from the sequential framework of turn-taking.not in tension with experience sharing but, instead, serves it.While our first hypothesis questions the relevance of turn-taking for experience sharing, our second hypothesis represents just the opposite view: it suggests that the sequential framework of turn-taking is contingent emotional reciprocity. It can thus be argued that contingent emotional reciprocity, and thus also experience sharing, can be facilitated by the sequential framework of turn-taking.Previously, we highlighted the significance of the automatic resonance processes for experience sharing. However, it has been pointed out that the mere reproduction of other people’s behaviors represents a closed loop system: it reflects what is already out there . So, forIn human ontogeny, the first instantiations of contingent emotional reciprocity appear in the context of alternation between approach and withdrawal tendencies . InfantsIn the subsequent development of the human infant, the experiences of contingent emotional reciprocity get more nuanced. Already from 2 months on, infants and their caretakers start to look and listen to each other more carefully; producing vocal, facial and gestural responses elicited by the expressed feelings and interests of their interaction partners . During From this perspective, let us consider Example wow, gosh, oh my good, ooh, phew have been described as interactionally organized performances, interactional achievements, instead of automatic emotional eruptions , then we would expect that there would be a tension between overlapping vocalizations and effective instrumental communication. While there is some evidence for the tension between turn-taking and experience sharing , the potAccording to the second hypothesis, turn-taking is in the service of experience sharing. In allowing the participants to engage in increasingly complex forms of joint action, and, hence, in ever more exciting shared experiences, there seems to be no tension between turn-taking and experience sharing. From this perspective, there seems to be a developmental continuity between the early infant-caretaker interactions governed by emotional reciprocity and the later, more complex forms of social interaction. If this hypothesis is valid, then there must be evidence that the instances of experience sharing cast in the sequential framework of turn-taking can, in principle, reach at least the same level of intensity as those occurring in the context of overlapping talk. Moreover, one would need to show that occurrences of experience sharing and instrumental goal-pursuit would be relatively evenly distributed between the instances of overlapping talk and talk abiding to the norms of turn-taking.No matter which of the above hypothese is more valid than the other, the relationship between experience sharing and turn-taking is something worth further investigation—something that this paper has sought to highlight.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Acidithiobacillus, Leptospirillum and Acidiphilium exhibited high transcriptional activities. Community-wide comparative analyses clearly showed that the AMD microorganisms adapted to the different environmental conditions via regulating the expression of genes involved in multiple in situ functional activities, including low-pH adaptation, carbon, nitrogen and phosphate assimilation, energy generation, environmental stress resistance, and other functions. Organism-wide comparative analyses of the active taxa revealed environment-dependent gene transcriptional profiles, especially the distinct strategies used by Acidithiobacillus ferrivorans and Leptospirillum ferrodiazotrophum in nutrients assimilation and energy generation for survival under different conditions. Overall, these findings demonstrate that the gene transcriptional profiles of AMD microorganisms are closely related to the site physiochemical characteristics, providing clues into the microbial response and adaptation mechanisms in the oligotrophic, extremely acidic environments.The microbial communities in acid mine drainage have been extensively studied to reveal their roles in acid generation and adaption to this environment. Lacking, however, are integrated community- and organism-wide comparative gene transcriptional analyses that could reveal the response and adaptation mechanisms of these extraordinary microorganisms to different environmental conditions. In this study, comparative metagenomics and metatranscriptomics were performed on microbial assemblages collected from four geochemically distinct acid mine drainage (AMD) sites. Taxonomic analysis uncovered unexpectedly high microbial biodiversity of these extremely acidophilic communities, and the abundant taxa of  The Earth's extreme environments harbor a wide array of microorganisms with the ability to survive and thrive in physical extremes . Analyziin situ metabolic activities and functional partitioning of microbes in these low-diversity communities. To date, the environmental transcriptomes of microbial assemblages in the Tinto River (Spain) ecosystem have been profiled using Leptospirillum ferrooxidans DNA microarrays  polymetallic ore  and another from the acidic drainage pond associated with the tailings impoundment at the Fankou (FK) Pb/Zn mine . The other two samples were collected from the Yunfu pyrite mine , one from the AMD Yunfu stream (YFS) draining across the surface mining area and the other from the AMD collection Yunfu pond (YFP) downstream before treatment. For DNA/RNA extraction, triplicate samples were collected on site by prefiltering through a 1.6-μm GF/A filter to remove impurities and then filtering through a 0.22-μm polyethersulfone filter using a peristaltic pump. Physicochemical characteristics were determined either on site or in the laboratory as previously described .Statistical enrichment of a given gene or COG between two data sets was determined by pairwise comparisons using two-tailed Fisher's exact test, with confidence intervals at 99% significance and Benjamini–Hochberg correction . Hierarchical clustering analysis was performed with correlation distance and average-linkage method using the R package of ‘pheatmap' .-1), and high concentrations of sulfate (6690–7931 mg l-1), total iron (520–2190 mg l-1) and heavy metals   and dissolved organic carbon (DOC) (2.9–6.8 mg l and Mn) , feature and Mn) . SpecifiAcidithiobacillus and Leptospirillum members , for elevated temperature should upregulate the expression of proteins associated with these functions  (kdpABC) , and glutamate, arginine and lysine decarboxylation   proteins, the transcriptional repressor LexA (lexA) and nucleic acid-binding proteins of Hu (hupB) and Dps (dps), were also expressed in all four communities  . In addi(kdpABC)  indicate protons . The cytA, cadA) . Moreovemunities . Our anator COGs . These rtor COGs .-1; Acidithiobacillus spp. and/or Leptospirillum spp. were the main carbon fixers in the analyzed AMD communities, as the genes encoding the key enzymes for Calvin–Benson–Bassham cycle and reductive tricarboxylic acid cycle were highly expressed  in all analyzed AMD samples. Therefore, the knowledge of nitrogen fixation and assimilation mechanisms used by the AMD microorganisms is critical to the understanding of how they respond and adapt to the nitrogen-limited conditions  in all the four communities (L. ferrooxidans (group I), L. ferrodiazotrophum (group III), At. ferrivorans and Acidithiobacillus sp. GGI-221. This result indicated the key role of these taxa in nitrogen fixation of the communities, despite the relatively low abundance of the nitrogen-fixation transcripts (5–27 transcripts). The genes for ammonium transporter (amt) showed high transcriptional activities in all communities (glnA) and glutamate synthase (gltBD), which would permit the incorporation of ammonium into glutamine and then to glutamate for utilization  exhibited very low transcriptional activities  were highly abundant in our cDNA data sets  that the AMD communities, especially that of YFP, which exhibited the highest expression levels of these genes  to uptake protons to generate ATP (2 to generate H2O with the consumption of electrons from ferrous iron (Fe2+) and/or sulfur oxidation , superoxide dismutase (sodA) and hydroperoxide reductase (dnaX), with the majority of which was associated with the active taxa , although those in DBS and YFP exhibited generally more similar activities  showed high activities in the uptake of phosphate. Moreover, At. ferrivorans in DBS and YFP may execute assimilatory sulfur reduction for the utility of sulfur as indicated by the upregulation of sulfite reductase genes of cysI, cysJ and cysH. Collectively, these lines of evidence indicate that At. ferrivorans in YFS contributed more for carbon, nitrogen and phosphate assimilation, whereas those in DBS and YFP were likely active in sulfur assimilation.The majority of the significantly different transcripts  compared with those in DBS and FK. For the carbon-fixation activity, all genes of the reductive tricarboxylic acid cycle in L. ferrodiazotrophum  were also detected, with the highest expression levels in YFS. These results suggest that this organism in YFS contributed much in the fixation of carbon and nitrogen via Fe2+ and sulfur oxidation, as At. ferrivorans did in the same community (see above). We further identified the genes for proteasome, which collectively accounted for a transcript abundance of 0.44%, 1.45% and 0.93% in DBS, FK and YFS, respectively  proteins and phage integrase proteins (Similar to those of fixation ; howeverotrophum , with a otrophum , and thootrophum . The genectively . Within ectively  and Leptproteins , implyinAt. ferrivorans and L. ferrodiazotrophum in YFS contributed more transcripts for carbon and nitrogen assimilation than their counterparts in other communities. The ecological significance of less active taxa, including their irreplaceable role for the whole-community function as well as their contribution in community assembly and dynamics, has been documented in marine environment (Our comparative metagenomic and metatranscriptomic analyses have provided a detailed gene transcriptional blueprint for the naturally occurring, low diversity microbial communities in the extreme AMD environments, demonstrating how these extraordinary microorganisms respond and adapt to the different physicochemical conditions at both community- and organism-level. The transcriptional analyses of dominant transcripts and indicator COGs revealed a high diversity of transcripts harbored by these acidophilic assemblages. These transcripts were associated with a wide range of functions, the expression levels of which were closely related to the physicochemical characteristics of the AMD systems. In particular, the detection of nitrogen-fixation transcripts provided clues for nitrogen-fixing activities in AMD communities. Detailed analysis of the transcriptional behaviors of the most active organisms revealed differential gene expression patterns, likely reflecting their distinct roles and life state in different communities. For example, both


There is an ongoing debate whether an impairment of visual attentional functions constitutes an additional or even an isolated deficit of developmental dyslexia (DD). Especially performance in tasks that require the processing of multiple visual elements in parallel has been reported to be impaired in DD. We review studies that used parameter-based assessment for identifying and quantifying impaired aspect(s) of visual attention that underlie this multi-element processing deficit in DD. These studies used the mathematical framework provided by the “theory of visual attention”  to deriv Visual attentional functions are currently discussed as being related to developmental dyslexia (DD), a disorder in written language acquisition, that cannot be explained by age, visual sensory problems, or inadequate reading instruction . Due to Especially performance in tasks that require the processing of multiple visual elements in parallel seems to be impaired in DD . This muOne influential theoretical concept focusses on general resource limitations. It is suggested that people with DD have a reduced visual attentional span, assessed as the amount of elements that can be reported from a briefly displayed array . CriticaAdditionally or alternatively, impaired attentional selectivity aspects, i.e., changes in spatial attention and/or inefficiency in filtering information could also account for deficient multi-element processing. Indeed, people with DD might not show a normal slight leftward attentional bias. It is known that patients with hemi-neglect following right parietal damage show a rightward attentional bias, which is shown, for example, in rightward deviations in line bisection tasks. Normal participants instead deviate slightly, but reliably toward the left when bisecting lines  and alsoIn this review, we explore the role of visual attention functions for impaired multi-element processing in DD. A critical methodological challenge is to identify and quantify the impaired function(s). Recently, a number of studies have used a parameter-based account of visual attention assessment . In thest0, (ii) by an object’s processing rate, which depends on the relative attentional weight it receives, and (iii) by the capacity of the VSTM store K . TVA provides parameters for characterizing the general processing efficiency of the information processing system , and for characterizing attentional selectivity .Within the TVA framework, the efficiency of visual selection performance of a given participant can be described on the basis of a set of mathematically independent, quantitative measures of attentional components , in which the visual perception threshold , the growth parameter reflects the rate at which the stimuli (objects) can be processed (parameter processing speed C: number of element/s), and the asymptote of the growth function indicates the maximum number of objects that can be represented within VSTM (parameter VSTM storage capacity K). Thus, estimating these parameters of interest here permits to further differentiate if a deficient visual span performance  and efficiency in prioritizing targets over distractors (parameter top–down control α). Parameter wλ is derived in report tasks that involve trials with presentation of stimuli in only one and trials with stimuli in both hemifields. Based on report individual accuracy differences in bilateral vs. unilateral displays, the TVA model produces estimates of attentional weights iw separately for the left (wL) and the right hemifield (wR), and wλ is then computed as wL/(wL + wR). Hence, a value of wλ = 0.5 indicates balanced weighting; values of wλ > 0.5 indicate a leftward and values of wλ < 0.5 a rightward bias. A slight normal “pseudo-neglect” is indicated by a value of wλ > 0.5, because weights for objects to the left of fixation are slightly higher than those for objects to the right. If participants with DD indeed show a reduced or absent pseudoneglect, this would be indicated by significantly higher λw values compared to control participants. Parameter α, representing efficiency of top–down attentional control, is estimated from the performance in partial-report tasks, where participants have to report target objects, only, which are prespecified , whilst ignoring distractors. The parameter indicates the relative attentional weights of distracters compared to targets (wD/wT). Impaired top–down control in participants with DD would be indicated by higher α-values compared to control participants, indicating relatively more attentional weight allocated to distracters. In sum, estimating these selectivity parameters permits the exploration of the potential contribution of lateralized deficits or inefficiency of top–down control to impairments found in DD.Furthermore, TVA-based assessment allows to individually estimate critical selectivity aspects of attention of interest here: spatial laterality . The speed reduction was replicated at group level, with similar degree in children and adults with DD , in line with findings from line bisection studies . Thus, the TVA-based analyses do not support the previously suggested assumption that multi-element processing deficits in DD result from an inability to prioritize relevant over irrelevant information (Concerning the second selectivity aspect assessed, the reviewed studies reviewed above indicate that top–down control is not impaired in DD (ormation .We summarized the results of studies that used TVA-based assessment of visual attentional parameters to examine a potential relevance of deficient visual attentional processing in DD. Taken together, in children and adults with DD  marked rThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


C. elegans to mammals, in the regulation of protein clearance via activation of FOXO transcription factors. In response to proteotoxic insults, TDP-43 redistributes from the nucleus to the cytoplasm, promoting nuclear translocation of FOXOs and relieving an inhibition of FOXO activity in the nucleus. The interaction between TDP-43 and the FOXO pathway in mammalian cells is mediated by their competitive binding to 14-3-3 proteins. Consistent with FOXO-dependent protein quality control, TDP-43 regulates the levels of misfolded proteins. Therefore, TDP-43 mediates stress responses and couples the regulation of RNA metabolism and protein quality control in a FOXO-dependent manner. The results suggest that compromising the function of TDP-43 in regulating protein homeostasis may contribute to the pathogenesis of related neurodegenerative diseases.Protein homeostasis is critical for cell survival and functions during stress and is regulated at both RNA and protein levels. However, how the cell integrates RNA-processing programs with post-translational protein quality control systems is unknown. Transactive response DNA-binding protein (TARDBP/TDP-43) is an RNA-processing protein that is involved in the pathogenesis of major neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Here, we report a conserved role for TDP-43, from  C. elegans to mammals. Under conditions of stress, TDP-43 translocates from the nucleus to the cytoplasm, competes with FOXO transcription factors for binding to 14-3-3 proteins, and releases FOXO for nuclear translocation and activation. These data are consistent with the ability of TDP-43 to regulate protein aggregation. Together the results provide important insight into the role of TDP-43 in stress responses and disease mechanisms. Since chronic stress is associated with neurodegenerative diseases, the TDP-43 switch could be kept in overdrive mode in these disorders, with its capacity to buffer further stress and maintain protein homeostasis being compromised. This mechanism also suggests that other RNA-processing proteins that exhibit similar stress-induced behavior may be coupled to other cellular pathways to provide coordinated reprogramming in stress responses.TDP-43 is linked to pathogenesis of major neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). How TDP-43 contributes to the development of these degenerative diseases remains unsolved, and the full range of TDP-43 functions has yet to be established. In the present study, we explored a conversed function of TDP-43 in regulating protein homeostasis from  A defining feature of all living cells is the ability to adapt to stress stimuli. This adaptive response is particularly important for maintaining protein homeostasis, which is critical for cellular functions. The cell employs a variety of protein quality control mechanisms in an effort to maintain the integrity of the proteome, including those regulating protein synthesis and degradation. The regulation of protein synthesis occurs at multiple levels, including transcription C. elegans, TDP-1, was shown to negatively regulate proteotoxicity associated with protein misfolding, suggesting that the nematode protein plays a role in the regulation of protein homeostasis TAR-DNA binding protein (TDP-43) is an RNA-binding protein that has been suggested to play a major role in the pathogenesis of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) C. elegans DAF-16 and mediate expression of genes involved in longevity, stress resistance, and protein quality control Despite extensive study of the complex pathways responsible for cellular stress responses, how the cell coordinates these different adaptive programs is not yet completely understood. In particular, the exact mechanisms by which RNA processing coordinates with other aspects of stress responses to maintain protein homeostasis remain unclear. Here, we present a mechanistic pathway through which TDP-43 couples RNA processing with active protein quality control during stress. Our results show that TDP-43 regulates the activities of FOXO transcription factors, which are orthologous to C. elegans lacking its sole TDP-43 ortholog, TDP-1, lives longer than wild-type (WT) controls (C. elegans to humans tdp-1(ok803lf);daf-2(e1370lf), exhibited a longer lifespan than did daf-2(e1370lf) alone ;daf-16(mu86lf), completely abolished the longevity effect of tdp-1(ok803lf) alone  alone . There ant alone . These df) alone  [55], inf) alone .C. elegans lacking TDP-1, the mutant also shows enhanced clearance of misfolded proteins tdp-1(ok803lf) mutant reduced the aggregation of TDP-C25-YFP, a misfolded protein reporter expressed in C. elegans neurons (tdp-1(ok803lf);daf-16(mu86lf). The daf-16 mutant reversed the reduction of protein aggregation conferred by the tdp-1 mutant (Correlating with increased lifespan in  neurons . To test1 mutant . This datdp-1(ok803lf) mutants and WT controls. These DAF-16-regulated genes included stress-resistance genes such as the metallothioneins mtl-1 and mtl-2 as well as uncharacterized genes dao-4, dct-8, and dct-17. The results indicated that most of the tested DAF-16 target genes are significantly up-regulated in tdp-1(ok803lf) mutant C. elegans  mutants and WT controls indicates that there are more genes down-regulated than up-regulated in tdp-1(ok803lf) mutants , with the first three showing a high degree of structural and regulatory similarity C. elegans DAF-16 activity by loss of TDP-1, shRNA-mediated knockdown of endogenous TDP-43 in HEK293T cells significantly increased the FOXO transcriptional activity, as indicated by the increase in luciferase activity  (Pearson's correlation coefficient>0.9) (Since NaCl treatment induced the nucleocytoplasmic translocation and granule formation of ent>0.9) . The redent>0.9) . ChangesInterestingly, we found that NaCl-stress-induced patterns of TDP-43 translocation and sequestration varied in a concentration-dependent manner. When HEK293T cells were treated with 0.3 M NaCl, TDP-43 underwent cytoplasmic translocation but was recruited to a previously undescribed, smaller type of granules that did not co-localize with G3BP (Pearson's correlation coefficient <0.4) . We alsoNext we explored whether the translocation of TDP-43 is a reversible process. After a 3-h treatment with sorbitol or NaCl, the stressors were washed off, and the cells were kept in normal medium. After 24 h, TDP-43 was completely translocated back to the nucleus, although G3BP-positive stress granules remained in the cytoplasm . These rSince redistribution of proteins in the cell is often associated with post-translational modifications, we examined how the phosphorylation of TDP-43 correlates with the changes in its localization induced by hypertonic stress. We used a phospo-TDP-43 Ser409/410-specific antibody to detect the phosphorylated TDP-43 in HEK293T cells by immunofluorescence microscopy . In untrTo understand how TDP-43 could regulate the activity of FOXOs during stress responses, we investigated the protein interactions that link these two proteins. We co-transfected HEK293T cells with tagged versions of the TDP-43 and FOXO3a proteins and performed co-immunoprecipitation assays. Immunoprecipitation assays using TDP-43 as bait failed to pull down FOXO3a , indicat2O2 treatment, cytoplasmic translocation of TDP-43 and nuclear translocation of FOXOs both increased, and their exclusive spatial correlation was maintained.Next we investigated whether TDP-43 and FOXOs are linked in their localization changes during stress responses. To easily visualize the localizations of FOXO proteins, we utilized two U2OS cell lines that stably expressed GFP-FOXO1 or GFP-FOXO3a. Interestingly, we observed a strong mutual exclusion in the nucleocytoplasmic compartmentalization of TDP-43 and FOXO proteins . Under n2O2 treatment, which increases the cytoplasmic fraction of TDP-43, the expression of TDP-43 led to a pronounced shift in FOXO3a from the cytoplasm to the nucleus  and a nuclear marker (PARP1) confirmed a clean separation of cytoplasmic and nuclear fractions. The expression of TDP-43 alone, without stress, did not induce any detectable change in the fractionation of FOXO3a. However, with 1 mM H nucleus . These r2 stress . Thus TD2O2 treatment, 14-3-3σ was able to pull down either TDP-43 or FOXO3a when 14-3-3σ was co-transfected with either of the two proteins  or the nuclear export signal (ΔNES) on the interaction between14-3-3 and FOXO proteins using the same competitive co-immunoprecipitation assays described above. The ΔNLS and ΔNES mutations enhanced the relative enrichment of cytoplasmic and nuclear TDP-43, respectively . The comFOXOs have been reported to positively regulate protein quality control systems, including proteasomes and autophagy In the present study, we have described a conserved signaling pathway in which TDP-43 senses stress and regulates protein quality control. This pathway is mediated, at least in part, by the ability of TDP-43 to regulate FOXO transcription factors. Therefore, TDP-43, a known RNA binding protein, represents a link between protein quality control and RNA metabolism, indicating a novel layer of regulation of protein homeostasis imparted by RNA-processing proteins. We propose that TDP-43 mediates stress responses designed to maintain protein homeostasis by coordinating the attenuation of protein synthesis and the selective enhancement of protein quality control systems. First, the loss of TDP-43 from the nucleus and its localization to stress granules in response to cellular stress constitute an adaptive response to keep target mRNAs from active translation C. elegans  strain, a transgene DNA construct was generated by subcloning TDP-1 cDNA with a C-terminal YFP tag into a modified plasmid, pPD30_38 , with the promoter replaced with that of the snb-1 gene, as previous described snb-1::TDP-C25-YFP(iwIs22) strain was reported previously All C. elegans and mutant strains RB929 [tdp-1(ok803)], CF1038 [daf-16(mu86)], CB1370 [daf-2(e1370)], IW417 , and IW177  were cultured under standard conditions at 20°C. Newly laid embryos were synchronized within 2 h and transferred to fresh NGM plates, with 50 embryos per plate. These animals were transferred to new plates every day until they reached the post-reproductive stage and were allowed to age under normal culture conditions. Animals were checked daily and considered dead if they showed no response to probing with a platinum pick. The animals that crawled out of the plate, had vulval burst, or died with internally hatched larvae or “bags of worms” were censored. The day when embryos were synchronized was defined as the first day for lifespan analysis. The lifespan data were analyzed using Prism 5 software.The WT N2 C. elegans were cultured at 20°C until they grow to L4 larval stage. L4 larvae were individually transferred to new plates and cultured at 25°C. Every 24 hours, these animals were transferred to new plates at 25°C until they stopped producing eggs. After transferring, the eggs laid on the plates were counted. For locomotion measurement, L4 larvae grown at 20°C were subject to a thrashing assay. The animals were transferred into M9 buffer  and allowed to adapt to the buffer for 1 min. Then the rate of body bending or thrashes for the animals was measured, with a thrash being counted when both the head and the tail bend over 45 degrees.C. elegans, animals were harvested and total RNA was isolated using a phenol-chloroform extraction with TRIzol reagent (Life Technologies), followed by purification with an RNeasy mini kit (Qiagen). A two-step RT-PCR was employed to assess relative changes in transgenic transcripts using an iScript cDNA Synthesis Kit and an IQ SYBR Green kit (Bio-Rad). Fluorescence was measured on a real-time PCR cycler (Bio-Rad), and CT values were analyzed based on standard curves. The worm gdh-1 gene was used as a control. The sequences of all the primers used are listed in the To quantify the expression of specific genes in Sal site and Gateway vector (pDonor-221) are listed in the HEK293T cells were grown in Dulbecco's modified Eagle's medium supplemented with antibiotics and 10% fetal bovine serum. Transient transfection of HEK293T was carried out with Lipofectamine 2000 according to the manufacturer's instructions (Life Technologies). The primers for subcloning TDP-43 cDNA into pRK5-myc vector at BamHI/HindIII restriction sites. The sequence of shRNA oligonucleotides (i), (ii), and (iii) as well as a control shRNA-RFP-C-RS are listed in the 5 per well, then transfected with the shRNA constructs after 24 h. After 24 h, puromycin was applied at 3 µg/ml to select for positively transfected cells, and cells were harvested at 72 h post-transfection.To knock down the expression of TDP-43, we generated shRNA constructs targeting different regions of the TDP-43 transcript and containing a puromycin resistance gene. The TDP-43 shRNA constructs were cloned by inserting small hairpin oligonucleotides matching TDP-43 mRNA sequences into the pRFP-C-RS plasmid (Origene) using Renilla luciferase, was used as an internal control. Cells were plated in 24-well plates at a density of 1×105 cells per well, and after 24 h, cells were transfected with expression plasmids of FOXOs, pSV40-Renilla, pGL3-FHRE-luciferase, or TDP-43. At 48 h, luciferase activities were measured by using the Dual-Luciferase Reporter Assay System (Promega) on a Synergy H1 luminometer (Bio-Tek). The experimental firefly luciferase activity was normalized to the control Renilla luciferase activity to reflect the FOXO activities.A reporter construct, pGL3-FHRE-Luc was originally from M. Greenberg (Addgene Plasmid 1789), which expresses the firefly luciferase driven by a promoter containing three copies of forkhead responsive elements, was employed to measure FOXO transcription activity In addition to HEK293T cells, two U2OS stable cells lines expressing FOXO1 or FOXO3a were used (Thermofisher). Cells were plated on coverslips pre-treated with polyethylenimine , in 6-well plates. Cells were stressed with 0.4 M sorbitol  for 1 h or 0.2 M (or 0.3 M) NaCl for 3 h. Coverslips were washed twice with 1× PBS and then fixed with 4% paraformaldehyde (PFA) for 10 min at RT. After the PFA was washed, the cells were permeabilized with 0.1% Triton X-100 in 1× PBS for 10 min. After treatment with blocking buffer containing 2% BSA in PBS with 0.1% Triton X-100 for 30 min, the coverslips were incubated with primary antibody at 4°C overnight. The primary antibodies were diluted in blocking buffer; they were: polyclonal anti-TDP-43, 1∶200 ; monoclonal anti-G3BP, 1∶200 ; and monoclonal anti-phospho TDP-43 (Ser409/410), 1∶200 . The coverslips were then incubated with secondary antibody for 1 h at RT: goat anti-rabbit Alexa Fluor 488, 1∶1000 ; goat anti-mouse Alexa Fluor 555, 1∶1000 ; or goat anti-mouse Alexa Fluor 555, 1∶1000 . The coverslips were mounted in buffer with 2.5% DABCO, 100 mM Tris-HCl (pH 8.8), 50% glycerol, and 0.2 µg/ml DAPI. Images were collected with a Zeiss AxioObserver Z1 with an Apotome imaging system.Cells were lysed in buffer containing 50 mM Tris-HCl (pH 8.0), 150 mM NaCl, 0.4 mM EDTA (pH 8.0), 1% NP-40, 0.05% sodium deoxycholate, and complete protease inhibitor cocktail (11836153001). Cell lysates were incubated with anti-HA antibody  overnight at 4°C before being centrifuged at 10,000× g for 10 min. Supernatant was transferred to clean tubes and incubated with protein G-Sepharose beads  for 1 h. After five washes with lysis buffer, the beads were resuspended in SDS sample buffer and boiled for 5 min before the eluted materials were subjected to standard western blot analysis: Protein samples were separated by SDS-PAGE and transferred to nitrocellulose membranes (Bio-Rad). The membranes were blocked with 5% milk in 1× phosphate-buffered saline with 0.1% Tween 20 (PBST) and incubated with the following primary antibodies: anti-c-myc- horseradish peroxidase, 1∶5000 ; monoclonal anti-c-myc, clone 9E10, 1∶3000 ; monoclonal anti-Flag M2, clone M2, 1∶5000 ; polyclonal anti-GAPDH,1∶30,000 ; monoclonal anti-V5, 1∶3000 ; polyclonal anti-TARDBP, 1∶3000 , polyclonal anti-PARP, 1∶1000 , polyclonal anti-Caspase 3, 1∶1000 , and polyclonal anti-Cu/Zn SOD, 1∶3000 . The following secondary antibodies were used: goat anti-rabbit IgG (H+L)-HRP conjugate, 1∶3000 ; goat anti-mouse IgG (H+L)-HRP conjugate, 1∶3000 ; goat anti-rabbit IgG IRDye, 1∶40,000 ; and donkey anti-mouse IgG, 1∶40,000 . After incubating with secondary antibodies, the membranes were developed on films or the Odyssey image system (Li-COR).2, 0.1 mM EDTA, 0.5 mM DTT, 0.4% NP-40, 0.5 mM PMSF, and complete protease inhibitor cocktail, then incubated on ice for 5 min. Cell lysates were then centrifuged at 600× g at 4°C for 3 min. Supernatants were transferred to clean tubes and saved as the “cytoplasmic fraction.” The pellets were washed twice with cytoplasmic extraction buffer and centrifuged at 600× g at 4°C for 3 min. After washing, the pellets were resuspended in a nuclear extraction buffer containing 20 mM HEPES (pH 7.9), 420 mM NaCl, 1.5 mM MgCl2, 25% glycerol, 0.5 mM PMSF, 0.2 mM EDTA, 0.5 mM DTT, and complete protease inhibitor cocktail and vortexed at room temperature for 1 min. The resuspended samples were incubated on ice for 10 min, then vortexed for 1 min and centrifuged at 16,000× g for 10 min. The supernatants were transferred to clean tubes and saved as the “nuclear fraction.”To isolate cytoplasmic and nuclear fractions, cultured mammalian cells were harvested in 1× PBS, centrifuged at 200× g for 1 min, and washed twice with 1× PBS. The cell pellets were resuspended in a cytoplasmic extraction buffer containing 10 mM HEPES (pH 7.9), 10 mM KCl, 1.5 mM MgClC. elegans were extracted in 200 µl of buffer containing 10 mM Tris-HCl (pH 8.0), 100 mM NaCl, 1 mM EDTA (pH 8.0), 0.5% NP-40, 50 µM iodoacetamine, and protease inhibitor  by using a Bioruptor ultrasonicator at 4°C for 5 min. The lysates were then transferred to an Airfuge ultracentrifuge (Beckman Coulter) and centrifuged at 25 psi  for 5 min.A biochemical assay was used to detect insoluble aggregated proteins according to a previously described protocol, with some modifications The supernatant was transferred to clean tubes and saved as the “soluble” fraction. The remaining pellet was again resuspended in extraction buffer, then sonicated for 5 min. This resuspended pellet was applied to the Airfuge and centrifuged at 25 psi for 5 min. The remaining pellet was transferred to 100 µl of resuspension buffer containing 10 mM Tris-HCl (pH 8.0), 100 mM NaCl, 1 mM EDTA (pH 8.0), 0.5% NP-40, 0.5% deoxycholic acid, and 2% SDS, and sonicated for 5 min. This fraction was considered the “insoluble” protein aggregate fraction.p values for comparing Kaplan-Merier survival curves between groups were calculated by the Log-rank test. p values of qPCR, egg-laying, locomotion and Luciferase assay data were calculated with the Student's t-test.Image J software was used to analyze the colocalization between TDP-43/pTDP-43 and G3BP, and the colocalization was measured by Pearson's correlative coefficient. Figure S1tdp-1(ok803lf), daf-2(e1370lf) and the tdp-1;daf-2 double mutant were subjected to assays quantifying egg-laying  (A) and locomotion  (B). Error bars represent SEM.Loss of TDP-1 improves egg-laying and locomotion defects in the absence of DAF-2. The WT control, (TIF)Click here for additional data file.Figure S2tdp-1-null C. elegans. (A) Loss of tdp-1 in C. elegans leads to more down-regulated genes than up-regulated genes. Transcriptional profile analysis of mutant C. elegans lacking tdp-1 as compared to wild-type N2 animals. There were 485 genes down-regulated (blue) and 227 genes up-regulated (red) when the threshold of -fold change (FC) was set at 1.5. (B) Quantitative RT-PCR validation of representative genes analyzed by the microarray assay (black dots) and the DAF-16 transcriptional targets (red dots).DAF-16 transcriptional targets are specifically up-regulated in (TIF)Click here for additional data file.Figure S3Renilla luciferase control. Cell lysates were subjected to dual luciferase assays, and the ratio of firefly to Renilla luciferase activity was used to indicate the FOXO transcriptional activity. n>3, p>0.05.The FHRE-Luc reporter is not affected by the transfection of TDP-43 alone. HEK293T Cells were co-transfected with Myc-TDP-43 or control Myc vector, the FHRE-Luc reporter, and the (TIF)Click here for additional data file.Figure S4The dynamic change in the TDP-43 recruitment to stress granules induced by 0.2M NaCl treatment. HEK293T cells were treated with 0.2 M NaCl and analyzed at different time points by immunofluorescence microscopy for distribution of the endogenous TDP-43 (red) and the stress granule marker G3BP (green). With 30 min of the treatment, TPD-43 is predominantly nuclear. At 1 h, TDP-43 gains a slight cytoplasmic distribution in a diffuse and small punctate pattern, while G3BP is localized to well-demarcated stress granules. At 2 h, cytoplasmic TDP-43 forms larger puncta and co-localizes with G3BP in stress granules. Scale bar: 5 µM.(TIF)Click here for additional data file.Figure S5The dynamic change in the TDP-43 recruitment to cytoplasmic granules induced by 0.3M NaCl treatment. HEK293T cells were treated with 0.2M NaCl and analyzed at different time points by immunofluorescence microscopy for distribution of the endogenous TDP-43 (red) and the stress granule marker G3BP (green). At 1 h, TDP-43 has a somewhat diffuse and minor punctate distribution in the cytoplasm, and fewer and smaller G3BP-positive stress granules are present when compared to the 0.2M NaCl treatment. At 2 h, the TDP-43 puncta remain small and do not co-localize with G3BP-positive stress granules. Scale bar: 5 µM.(TIF)Click here for additional data file.Figure S6The hypotonic stress-induced translocation of TDP-43 from the nucleus to the cytoplasm is reversible. HEK293T cells were treated with 0.4 M sorbitol, 0.2 M NaCl, or 0.3 M NaCl. After 3 h of treatment, the stressors were removed, and the cells were cultured for another 24 h. Immunofluorescent staining was performed for endogenous TDP-43 (red) and the stress granule marker G3BP (green). TDP-43 is translocated back to nucleus, although G3BP-positive stress granules remain. Scale bar: 5 µM.(TIF)Click here for additional data file.Figure S7TDP-43 does not physically interact with FOXO proteins. HEK293T cells were co-transfected with Myc-TDP-43 and either WT Flag-FOXO3a (A) or Flag-FOXO3aAAA, which is a constitutively active form of FOXO3a (B). Co-immunoprecipitation was performed using anti-Myc (TDP-43) antibody for the pull-down, and the precipitates were analyzed by western blotting using anti-Myc-TDP-43 and anti-Flag-FOXO antibodies. No interactions between TDP-43 and the FOXO proteins were detected.(TIF)Click here for additional data file.Figure S8Differential cellular distribution of TDP-43 WT and mutants lacking the nuclear localization signal (ΔNLS) or the nuclear export signal (ΔNES). (A) Schematic diagrams of TDP-43 proteins with ΔNLS or ΔNES mutations. The other domains of TDP-43, including the RNA recognition domains (RRM) and the glycine-rich domain, are shown. (B) TDP-43 ΔNLS or ΔNES mutant proteins have enriched cytoplasmic or nuclear localization, respectively. HEK293T cells were transfected with the V5-TDP-43 WT, ΔNLS, or ΔNES construct. Fractionation assays were performed as described in (TIF)Click here for additional data file.Table S1Primers and oligonucleotides in materials and methods.(DOCX)Click here for additional data file.


The adsorption energy between NH4 and graphene increased stage by stage which showed NH4 was a strong donor. The calculation suggested that H2O molecule could help a quick desorption of NH4 from graphene by converting NH4 to NH3 or (NH3)n(H2O)m groups, which was consistent with the experimental results. This study demonstrates that the ammonia gas produced by a bubble system of ammonia water is mainly ammonium groups of NH3 and NH4, and the NH4 moleculars are ideal candidates for the molecular doping of graphene while the interaction between graphene and the NH3 moleculars is weak.The gas sensor based on pristine graphene with conductance type was studied theoretically and experimentally. The time response of conductance measurements showed a quickly and largely increased conductivity when the sensor was exposed to ammonia gas produced by a bubble system of ammonia water. However, the desorption process in vacuum took more than 1 h which indicated that there was a larger number of transferred carriers and a strong adsorption force between ammonia and graphene. The desorption time could be greatly shortened down to about 2 min by adding the flow of water-vapor-enriched air at the beginning of the recovery stage which had been confirmed as a rapid and high-efficiency desorption process. Moreover, the optimum geometries, adsorption energies, and the charge transfer number of the composite systems were studied with first-principle calculations. However, the theoretical results showed that the adsorption energy between NH Furthermore, ammonia detection has good prospects in medicine diagnose. For instance, measurements of exhaled ammonia may differentiate between viral and bacterial infections in lung diseases to justify the use of antibiotics , and ammifficult . Hugo E nterface . Lakshmagraphene . Howevergraphene .4 and graphene is much stronger than that of ammonia groups NH3. We take the view that hydrogen atom plays an important role in the adsorption between NH3 and graphene, and we find that H2O helps NH4 to take off one hydrogen atom and achieves a rapid desorption from graphene sheets.These explanations revealed the truth from some degree, but some of these explanations are still not theoretically grounded or lack experimental verifications. Therefore, it is hard to treat them as a fully complete conclusion. In this work, we studied the adsorption and desorption of ammonia groups on graphene theoretically and experimentally. Our study demonstrates that the interaction between ammonia groups NH2 (300 nm) layer working as the sensors’ bottom gate through a dry transfer procedure [N) in a graphene film was determined with micro-Raman scattering using the shape of the 2D Raman band at ~2700 cm−1 and the intensity of the Raman-active G-band scattering at ~1585 cm−1 by a LabRAM XploRA with 532-nm excitation and low power which results was confirmed as a single-layer graphene. Then, the Cr(5 nm)/Au(100 nm) electrodes, used as the source and the drain electrodes of graphene-FET with channel width of 10 μm . A sensing test cycle typically consists of three consecutive steps that include exposures of the device to (i) vacuum environment to record a base value of the sensor conductance, (ii) target gas to register a sensing signal, and (iii) vacuum environment for the sensor recovery. All the electrical measurements were carried out at room temperature. Five different sensors for the same process were measured which showed similar behaviors except the magnitude of conductance (the difference is less than 10 %) and each measurement was repeated for at least five times.A pristine graphene was first prepared by mechanical exfoliation (repeated peeling) of small mesas of highly oriented pyrolytic graphite, which was then transferred to highly p++ doped silicon wafer with a thermally formed SiOrocedure , 11. TheTheoretically, the density functional theory (DFT) calculations were performed with CASTEP ; the gen−1) was observed in graphene indicating that the quality of the graphene was maintained during the transfer, and the ratio of intensity G peak and 2D peaks was about 0.5, which was a typical value of single-layer graphene. The basic electrical properties of bottom-gated bilayer graphene FETs were first studied in the atmospheric environment. We found that the Dirac peak was about 60 V (VD = 60 V) . Prolonged vacuum treatment was capable of removing the adsorbed air molecules strongly. The total amount of effective charged impurities can be simply estimated by the amount of Dirac voltage shift, VD, using the following expression [The pristine graphene was prepared by mechanical exfoliation, and the Raman measurement was applied to study the layer numbers of graphene in room temperature under the atmosphere. In Fig. pression :1\documeCgs is the capacitance of the SiO2 between the graphene and the silicon substrate  and e is the unit charge. From Fig. 12/cm−2 in the air, while that is about 0.43 × 1012/cm−2 in the vacuum, with the corresponding Dirac voltage point decreased from 60 to 6 V. Moreover, for each trace in Fig. Kh and Ke) from which one can extract the mobilities for holes (electrons) according to [where rding to :2\documeC is a constant related to electrode geometry structure and dielectric material of the device, K is the slope of linear region , and μ is the mobility (μh for hole and μe for electron). From the above expression, the mobilities of the hole and electron were almost same and which value was about 2000 cm2(V•S)−1.where 2O is an acceptor (hole doping) molecule [2O was turned off and evacuated within about 5 s, the conductance quickly decreased toward its baseline in 1 min, which illustrates that the force between graphene and water molecules is relatively weak [The response of graphene gas sensor to high-purity argon (higher than 99.99 %) was first measured and there was no obvious change in conductance. Then, the time response of the sensor’s conductance to a mixture gas (the relative humidity is ~85 %) by diverting dry argon air through a water bubbler bottle was measured, and the results were shown in Fig. molecule . When thThe conductance of the gas sensor increased ~22.5 % when exposed to 5 ppm ammonia, shown in Fig. 3 molecules should physisorb to the film without significant change of the band structure, and only a slight charge transfer of 0.03 − 0.04 e per adsorbed NH3 molecule was predicted to occur [Ea) means stronger binding between molecule and graphene. The Ea between the gas molecule and graphene is defined asTheoretical calculations on isolated defect-free graphene predicted that NHto occur . It seemto occur , 19. In to occur . The conEsystem is the total energy of the optimized equilibrium configuration of the graphene and the adatom; Egraphene is the total energy of the isolated graphene; Emolecule is the total energy of the corresponding adsorption molecules in its ground state; n is the number of gas molecules in the system.where 2O molecule starting from the O atom, the H-O bonds pointing parallel to the graphene surface (P) [2O-graphene group for different H2O positions with sheet-adsorbate distances of 3.6 Å  as well as that in H2O-graphene group, and the charge transfer, however, was solely determined by the orientation of the NH3 molecule. There was a slight charge transfer of 0.02 e from the molecule to the graphene surface in the U orientation and a extremely slight charge transfer (0.01 e) from graphene to NH3 molecule in the D orientation, and the bottom atom of the physisorbed molecule was located 3.4–3.6 Å  , and two6 Å Fig. b, and onsmall 31–5 meV as 3 molecules on graphene [3 are not good candidates for effective molecular doping of graphene. Obviously, there are other chemical groups that physisorb more strongly on graphene sheets and shift the Fermi energy inside the valence or conduction bands. Bradley et al. found that vacuum-degassed SWNT-FETs were insensitive to NH3; they suggested that to detect NH3 gas in the FET response, one should dissolve the NH3 in a H2O monolayer which forms on the nanotube FETs under ambient lab conditions. They proposed that the NH3 molecule in this environment could become a cation with the charge compensated from the SWNTs, i.e., acting as an n-dopant [3 molecules and hydrogen adatoms to generate chemical species that have stronger interactions with the graphene layer. Specifically, an isolated H impurity on graphene can be captured by an NH3 molecule in an exothermic reaction that releases 1.00 eV of energy [These results were in agreement with those already reported in previous studies on the binding energies of physisorbed NHgraphene , 6. All n-dopant . In factn-dopant , 22, plaf energy .4 species on a defect-free graphene layer was calculated in different graphene positions and a special orientation [4 hydrogen atoms pointing toward the graphene sheets, while the other two hydrogen species are on the other side of the ammonium group, see Fig. 4 molecule were adsorbed on graphene in a stronger manner, and the interaction between dangling bonds of graphene and NH4 was very strong and partial electron transfer occurs from graphene. The adsorption energy was 528–644 meV which was much larger than that of NH3 and H2O adsorbed in graphene sheets, and a huge charge transfer (0.19–0.54 e) from NH4 to graphene proved that physisorbed NH4 acted as a stronger donor for the basal plane of graphene, and the bottom atom of the NH4 was located 2.19 Å  for all of the systems are calculated in Fig. 3 molecules and graphene from first-principle calculations. The electronic structure and electrical conductivity of the intrinsic graphene have limited changes due to the adsorption of NH3 molecules. Moreover, this study found that the ammonium (NH4) had strong interactions with graphene, forming a strong bond that introduces a large amount of shallow donor states into the system. When adding water molecules into the desorption process, the whole desorption process was greatly accelerated. We considered that ammonium molecules and water molecules generated the ammonia-water cluster and found that the cluster has weak adsorption with graphene sheets by calculation. The results are in accordance with the experiment. In a word, this study demonstrated that the ammonia gas produced by a bubble system of ammonia water were mainly molecular groups of NH3 and NH4, and the NH4 moleculars are ideal candidates for the molecular doping of graphene. However, the NH3 moleculars have weak interaction with graphene.In conclusion, the adsorptions of ammonia on graphene were investigated with experiment and first-principle calculation. The study demonstrates that the remarkable variation of the electrical conductivity is induced by the ammonia adsorption, and that the graphene gas sensor possesses an excellent characteristic of high sensitivity for ammonia gas detection. It was found experimentally that ammonia molecules produced by a bubble system of ammonia water were strongly adsorbed onto the graphene sheets; however, ammonia molecules were only weakly adsorbed onto the intrinsic graphene with small binding energy value and large distance between the NH