Understanding the basis of brain function requires knowledge of cortical operations over wide-spatial scales, but also within the context of single neurons. In vivo, wide-field GCaMP imaging and sub-cortical/cortical cellular electrophysiology were used in mice to investigate relationships between spontaneous single neuron spiking and mesoscopic cortical activity. We make use of a rich set of cortical activity motifs that are present in spontaneous activity in anesthetized and awake animals. A mesoscale spike-triggered averaging procedure allowed the identification of motifs that are preferentially linked to individual spiking neurons by employing genetically targeted indicators of neuronal activity. Thalamic neurons predicted and reported specific cycles of wide-scale cortical inhibition/excitation. In contrast, spike-triggered maps derived from single cortical neurons yielded spatio-temporal maps expected for regional cortical consensus function. This approach can define network relationships between any point source of neuronal spiking and mesoscale cortical maps.DOI:http://dx.doi.org/10.7554/eLife.19976.001 Neural activity ranges from the microscale of synapses to macroscale brain-wide networks. Mesoscale networks occupy an intermediate space and are well studied in cortex forming the basis of sensory and motor maps . These nWe combine extracellular recordings of single units in the cortex, thalamus, and other sub-cortical sites with mesoscopic functional imaging in transgenic mice expressing the calcium indicator GCaMP . While s2+ binding and unbinding kinetics of GCaMP6, we expect imaging dynamics will be prolonged compared to actual spike records. In some cases, we employed deconvolution  calculated for each pixel within a time window of ±1 s. This peak method is a better reflection of correlated activity than the average over the ±1 s interval which would smooth out highly activated – but short duration activity increases. This method revealed that the activity recorded from a single right barrel cortex neuron yielded an STM showing strong and specific GCaMP signal in the barrel and motor cortices of both hemispheres  by imaging Thy-1 GFP-M mice (n = 6 mice) that lacked calcium-dependent neuronal fluorescent signals and failed to produce functional maps using the same procedures . To inveBy combining wide-field calcium imaging and single unit recording, the mesoscopic network associated with any neuron of the brain can be mapped. After establishing the method, we then focused on thalamic and cortical recordings of spiking neurons and confirmed their anatomical location by labeling probes with Texas red-dextran or DiI to visualize tracks . We obseWe have also assessed other means of generating event triggered maps including Multi-Unit-Activity (MUA) and local field potential (LFP) frequency bands. Cortical and thalamic STMs computed from single unit activity or MUA strongly resembled one another and did not vary greatly according to laminar depth. LFP-triggered STMs for delta band activity were similar to STMs, while those associated with higher frequency bands showed more unique patterns that will be investigated in future work . Delta bSTMs for single thalamic neurons indicated not only a functional link between GCaMP maps and their consensus cortical projection areas  but alsoTo determine quantitatively how cortical/sub-cortical STMs were related to intra-cortical networks, static STMs were compared using cross-correlation with a cortex-wide library of seed pixel correlation maps (SPM)  generateTo better understand the underlying structural circuit basis of distinct thalamic STMs, we examined the Allen Mouse Brain Connectivity Atlas  as in ouBy analyzing the cortical GCaMP signal, time courses corresponding to single neuron firing (firing= time 0) we observed dynamic cortical activity states –4. We deOur analysis indicates that averaging GCaMP cortical motifs from all spikes of a single cell produces converging STMs and STMTDs. However, thalamocortical synapses are known to be prone to synaptic depression and burst pattern firing may yield altered cortical responses . It is cWhile our analyses have employed spike-triggering averaging, spike-triggered co-variance  or variapattern #1: spike-triggered-excitation; pattern #2 spike-triggered inhibition; pattern #3 inhibition-triggered spiking followed by inhibition  and 20% triggered inhibition (pattern #2). In contrast, only 20% of thalamic neurons associated with post-spiking cortical excitation, while 80% of were associated with cortical inhibition patterns (45% with pattern #2% and 35% with pattern #3). Notably, pattern #3 was only identified with subcortical neuron spiking. Neither cortical cell depth, subcortical cell location (e.g. VPM vs VPL), nor cell-type classification (inhibitory and excitatory types ) revealeThe profile of STMTDs across all mice and recordings were also presented by aligning their peak activation (red) or peak depression (blue) in various bilateral ROIs that span wide and varied regions of cortex . The anaOur goal is to assess cortical functional connectivity based on coincidence between individual neuron spiking and ongoing spontaneous activity. However, we concede that in awake animals activity is rarely entirely spontaneous and that periods of volitional activity are present interspersed with relatively quiet intervals. Qualitative observations indicate limb twitches as well as tail and facial movements. In order to evaluate the impact of body movement on mapping, STAs were generated from spikes during periods of quietness and compared with STA from all spikes . Period 0 by more than 1/10 of the maximum ΔF/F0. We provide examples of the strategy being employed  than postsynaptic potentials evoked by a single synaptic connection (time to peak ~20 ms) . Slower equences . STMTD kequences , or geneequences  or glutaequences .We acknowledge that the same approach can be extended to making STMs during specific behaviors. During specific behaviors we do not expect major shifts in area map boundaries found during spontaneous activity, as we believe these are largely determined by projection anatomy  and in tWe conclude that the analysis of single neuron spiking activity can reliably reflect mesoscale activity transitions within mouse cortex. STMs together with connectomic information  may helptm1(cre)KrjEmx1/J, Jax #005628), CaMK2-tTA (B6.Cg-Tg(Camk2a-tTA)1Mmay/DboJ, Jax #007004) and TITL-GCaMP6f HzeIgs7/J, Jax #024103) strain (tm1(cre)KrjEmx1/J, Jax #005628), CaMK2-tTA (B6.Cg-Tg(Camk2a-tTA)1Mmay/DboJ, Jax #007004) and TITL-GCaMP6s HzeCg-Igs7/J, Jax #024104) strain. Transgenic GCaMP3 mice (n = 8) were produced by crossing Emx1-cre and R26-GCaMP3 HzeGt(ROSA)26Sor/J, Jax #014538) strain  were approved by the University of British Columbia Animal Care Committee and conformed to the Canadian Council on Animal Care and Use guidelines and animals were housed in a vivarium on a 12 hr day light cycle (7 AM lights on). Most experiments were performed toward the end of the mouse light cycle. Transgenic GCaMP6f mice , were produced by crossing Emx1-cre (B6.129S2-) strain . Transge) strain . The pre) strain . Control) strain . Given tMice were anesthetized with isoflurane (1.5–2%) for induction and during surgery and a reduced maintenance concentration of isoflurane (0.5–1.0%) or urethane was used later during anesthetized data collection. In some cases, animals were allowed to wake up following isoflurane anesthesia for awake imaging . Throughout surgery and imaging, body temperature was maintained at 37°C using a heating pad with a feedback thermistor. For cortical experiments, mice were placed on a metal plate that was mounted on a macroscope. The skull was fastened to a stainless steel head-plate and was connected with tubing to a water pump, which circulated temperature controlled 37°C water to ensure physiological temperature. A 9 × 9 mm bilateral craniotomy  covering multiple cortical areas was made as described previously . For subFor initial glass pipette recordings, the pipette was advanced into the targets  on the cortical surface (within the right hemisphere) at an angle of 30° from the horizontal using a motorized micromanipulator . Signals were recorded through a silver wire placed inside the micropipette and were amplified  and digitized at 12.5 kHz . A reference electrode, teflon-coated, chlorided silver wire (0.125 mm) was placed on the right edge of the craniotomy. For multichannel 16-channel laminar electrode  recordings, the electrode was directed toward the center of the burr hole using a motorized micromanipulator . The electrode was inserted into the right hemisphere with a 45° angle from the lateral surface of the cortex to avoid contact with the region where wide-field imaging was performed. The electrode was first held in cortex (BCS1) for cortical recordings and then advanced into the sub-cortical areas. The multichannel signal was amplified using 16-channel data acquisition system  and recorded for at least 5 min for each recording site. To minimize tissue damage, all experiments were performed by only a single insertion of the laminar electrode, and most trajectories were from barrel cortex to thalamus.Images of the cortical surface were recorded through a pair of front-to-front video lenses  coupled to a 1M60 Pantera CCD camera  . To visuIn some experiments (as indicated), we employed a multi-wavelength strategy to correct for potential green epifluorescence signals that were associated with non-calcium dependent events. We employed a variant of the elegant spectral correction strategy described by others  that monTo initiate wakefulness isoflurane and oxygen were stopped and the anesthesia mask was removed. Calcium imaging data were obtained over the following 1 hr. The body temperature of mice was maintained with a heating pad. Awake calcium imaging of spontaneous activity was performed in the absence of visual and auditory stimulation. A behavioral monitoring camera was used to confirm that the mice were indeed awake and relatively unstressed as grooming and whisking were occasionally observed. An analgesic, buprenorphine, was injected  24 hr before awake calcium recordings. We used a second Dalsa 1M60 camera (150 Hz) or Raspberry Picam’s RGB sensor (60 Hz) to capture body and whisker movements under infrared illumination.While relatively few large body movements were observed during awake imaging sessions, their impact on mapping was evaluated by generating STA from period of quietness. To identify regions of movement or quietness, the standard deviation of luminance fluctuation was calculated for each pixel. This approach showed that most of the movements were localized on the facial (whisker and jaw) and forepaw regions. A region of interest was manually drawn for each frame and the sum of absolute value of the gradient was calculated by subtracting each frame by their previous within this region. This gradient profile within the region of interest was temporally smoothed at 0.1 Hz, and the median and standard deviation were calculated (σ). Periods of quietness were identified as having a gradient lower than [median+σ/10], while periods of movement were higher than [median+σ]. To more selectively identify periods of quietness isolated from any movement, an exclusion window of 10 s was applied at the beginning and the end of each period of quietness and only periods of more than 10 s were kept. STA was then generated only from spikes for periods of quietness and compared with STA of all spikes.Sensory stimuli were used to confirm sensory cortical and sub-cortical areas using forelimb, hindlimb, whisker and visual stimulation. To stimulate the forelimbs and hindlimbs, thin acupuncture needles (0.14 mm) were inserted into the paws, and a 0.2–1 mA, 1 ms electrical pulse was delivered. To stimulate a single whisker (C2), the whisker was attached to a piezoelectric device  and given a single 1 ms tap using a square pulse. The whisker was moved at most 90 μm in an anterior-to-posterior direction, which corresponds to a 2.6° angle of deflection. A 1 ms pulse of combined green and blue light was delivered as visual stimulation. Averages of sensory stimulation were calculated from 20 to 40 trials of stimulation with an inter-stimulus interval of 10s.Raw extracellular traces were imported into Spike2  or SpikeSorter software  for spik0 was then performed by subtracting and dividing the baseline to each frame for each spike within a time window of ±3 s. We tested additional methods for computing ΔF/F0 including computing baseline from the average of the entire recording or band pass filtering the data (0.1 Hz to 6.0 Hz) but the results were similar. STA (spike-triggered average) sequences were created by averaging the ΔF/F0 responses for each trial and were compared with random spike STA. STA maps (STM) were then defined as the maximum response calculated for each pixel within a time window of ±1 s.TIF files of raw fluorescence were imported and processed using Matlab  or Python2.7 custom codes. For each spike, we averaged the cortical fluorescence of every pixel during the period preceding the spike (−3 to 0 s: baseline). ΔF/FSTM temporal dynamics (STMTDs) were defined as the time course of activity of the maximally activated pixel in a region of interest. The resulting clusters were separated using k-means clustering algorithm. Putative cell classification into inhibitory and excitatory cell types was based on the full-width-half-max of each unit's positive and negative phases .To calculate seed pixel correlation maps (SPM), the contribution of global and illumination fluctuations was subtracted from the signal of each pixel  and the http://connectivity.brain-map.org/, While the shorter blue wavelength light will scatter more than a green strobed reflected light signal used by others , our analysis of green reflected light and short blue reflected light, indicating that two were highly correlated, suggests that the major artifacts we observe are associated with large blood volume changes in superficial cortical layers.”See amended text from Results section:“Other potential sources of error include apparent changes in GCaMP6 signal due to alterations in blood volume or oxygenation . […]Furthermore thalamic STA maps and STA dynamic plots still indicated cases where thalamic spiking was associated with cortical inhibition. For these reasons we have attempted to correct other STA maps using this multi-wavelength procedure.”The second concerns the nature of the STM calculated from temporally isolated spikes versus spikes that are part of a burst. Given the known depression of thalamo-cortical synapses, this could likely contribute the variability of the STM data using thalamic spikes. To address this issue, the thalamic bursts can be isolated from the spike records and, as one possibility, the STM can be computed with respect to only the first spike.It is conceivable that averaging over many spikes could mask spatial heterogeneity observed in sub-groups of spikes. Therefore, we performed additional analyses where we classified spike triggered STMs and STMTDs into sub-groups based on spiking modes (bursting vs. tonic) or motif similarity in a high-dimensional space – with the goal of determining whether during different types of active cortical dynamics our single spike-sorted neurons contribute different types of STMs or temporal dynamics –5.We searched for STM sub-groups by dividing all spikes from a single cell into bursting versus tonic modes. We implemented methodology previously described for defining the main spiking modes of a single cell . Briefly, the method requires computing the distribution of each spike’s inter-spike-interval (ISI) between the previous (x-axis) and following (y-axis) spike . The res0 value – which is expected when averaging all spontaneous motifs (or frames) during a recording  groups by similarity and after removing the spontaneous component we were able to recover the all-spike average STMs . The resWe further applied this partitioning method on additional cells: two cortical and two thalamic cells with similar results . We alsoSee amended text from Materials and methods:“Cell Spiking Mode Determination. We implemented methodology previously described for defining main spiking modes  . […]We provide additional examples of this STM partitioning using other cortical and thalamic cells and also an example where we partitioned the STM distribution into 12 sub-networks but still recovered the all-spike average STM from each of the partitioned networks .”See amended text from Results section:“Our analysis indicates that averaging GCaMP cortical motifs from all spikes of a single cell produces converging STMs and STMTDs. […]These tests confirm that the averaging method reveals how single cells participate in largely stereotyped networks despite the variability of ongoing cortical activity.”Lastly, the "spontaneous activity" may currently include sensory-evoked activity from body motion. As the authors recorded body motion, it would be germane to check if "spontaneous activity" in fact results from self motion, as this changes the interpretation of "spontaneous activity' from internally generated to reafferent driven.Mice when habituated to our head-fixed recording apparatus do not exhibit extensive active body movements. However, the reviewer’s point is well-taken and we explored the potential contribution of active movements, however minute, to our recordings of spontaneous data. In new analysis, we now use simultaneously acquired video imaging (webcam) data to segment quiet periods of animal activity for spike-triggered averaging. Despite this procedure, we found little difference in spike-triggered mapping when movement periods were removed from awake mouse spontaneous activity data .See amended text from Materials and methods:“While relatively few large body movements were observed during awake imaging sessions, their impact on mapping was evaluated by generating STA from period of quietness. […] STA was then generated only from spikes for periods of quietness and compared with STA of all spikes.”Amended section from Results section:“Our goal is to assess cortical functional connectivity based on coincidence between individual neuron spiking and ongoing spontaneous activity. […] Therefore, brain imaging activity obtained in awake states is mostly indicative of a quiet awake state and is not primarily movement-related activity.”Reviewer #1:[…] Major issues:1) Results section. Spike-trigger averaging of optical signals was originally reported by Grinvald lab and authors are simply adopting this approach to the large-scale GCaMP imaging. Authors need to introduce the original work in the Introduction and/or Results section.Although we have referenced these papers, including within the Introduction, we agree that we could do more to highlight their seminal contributions that include the use of early application of spike-triggered averaging wide field imaging methods and conclusions. We have now revised our Introduction section to better acknowledge this pioneering work.The amended Introduction now states:This work extends pioneering studies investigating the relationship between single neuron spiking and local neuronal population activity assessed by voltage-sensitive dye imaging. […] Furthermore, we employ multisite, long shank, silicon probe recordings of single neuron activity that facilitates the assessment of long-distance activity relationships between remote subcortical single neuron activity and mesoscale cortical population activity.We also do note differences between our GCaMP wide-field mouse approach and the previous work in visual cortex. Notable differences include the neuronal specificity of the GCaMP imaging signals, as well relatively wider field of view and additional information concerning sub-cortical spiking neurons.2) ΔF/F). In addition, a single spike in a single neuron is unlikely to effectively activate all the post-synaptic neurons. Thus, it is possible that multiple-spike events (or bursts) can produce a more reliable STM. The authors could test this possibility by reanalyzing data and the results could be shown as in The reviewer raises an important point regarding the potential nuanced relationship between the pattern of cell firing and the efficacy in producing a reliable STM. The reviewer suggests that in the case of GCaMP imaging, individual spikes may not go readily detected. We reference papers which show that GCaMP6 can detect individual spikes in vivo . However, we feel we must clarify that our intention is not to imply a causal relationship between the unitary contributions of a single cell’s spiking activity to mesoscale cortical calcium activity or that our method requires the faithful detection of individual spikes. Instead, we interpret the single cell spiking activity as being correlated with the activation of these large cortical networks and likely acting in synchrony with other cells. However, the issue of averaged cell firing pattern diversity and its impact on STMs is important and explored in greater detail in our response to the Essential Revisions Comment #3.3) The reviewer raises an excellent point and it is not our intention to imply that a single spike is always linked to a single type of network motif but rather that the average response yields a pattern consistent with these consensus maps. However, one of our principle conclusions is that numerous, diverse sub-networks of cortical activity patterns exist and can be linked with the activity of a single cell as illustrated in 4) As mentioned, given the strong agreement between seed pixel maps and single neuron spike-triggered maps in cortex, we do not expect a lot of averaged-STM diversity. In the original submitted manuscript we provided “contour” plot analysis and quantification of individual STM maps across laminar depth . We founAnother consideration is that we insert the electrode using an angular tilt (45°) to achieve an approximately vertical penetration to the curved cortical surface such that the electrode is roughly recorded in the same functional cortical column. In the same functional column, the single neuron related functional maps may be more likely similar, even there are diverse cell types. We have also replaced the bar graph in Reviewer #3:[…] 1) The authors show that seed pixel correlation maps (SPMs) are better matched to cortical single-unit spike-triggered maps (STMs) than to thalamic STMs, and that thalamic STMs are generally more diverse than cortical  STMs. However, as suggested by the authors in the Discussion, this is likely due, at least in part, to greater diversity across thalamic recordings from neurons in a larger number of smaller thalamic nuclei  vs. recordings in a single cortical area with a large magnification factor. Further, cortical neurons within S1 are highly correlated, likely more so that nearby neurons in thalamus, further ensuring strong correlation between the cortical spiking activity and the SPM maps , more so that would be likely be possible with most thalamic units). The other suggested explanations for these findings made by the authors in the Discussion are far more speculative, and many would be difficult to test. Further, little effort is made to relate specific thalamic recordings from specific areas to any specific cortical patterns . Given that the correlation between cortical neurons and their neighbors is likely very different than the correlation between single thalamic neurons and their neighbors, it might be helpful to compute STMs for multiunit activity in cortex and in thalamus for a given electrode contact, and then subtract a scaled version of this STM from the single unit STM – that may put the cortical and thalamic analyses on more even footing . Similar analyses could be done for high-passed LFP or CSD recordings, allowing a better sense of the relationship between a single neuron's spike with network activity, vs. the correlated spiking of that neuron and many nearby neurons. This analysis may also reveal more spatially localized patterns . Similarly, for cortical recordings, one could subtract STMs in superficial recordings from STMs with simultaneously recorded neurons in deep layers, thus removing the 'columnar' component of the correlation, and allowing evaluation of residual, layer-specific contributions.Reviewer 3 is generally positive about the work and appreciates the linkage between wide-scale cortical activity and studies which have examined event-related activation using fMRI imaging.The reviewer makes a number of good points, mostly about better examining the relationship between individual neurons and the ensemble brain activity.1) The reviewer wonders about our interpretation of findings which compare diversity in cortical spike-triggered GCaMP maps for spike trains produced by cortical versus sub-cortical neuron groups. They acknowledge our discussion points, including diversity being attributed to the physical layout of the thalamus versus cortex and the ability to record from potentially more diverse neurons in the thalamus given the relatively smaller structure over which things are mapped. Accordingly, they suggest experiments to place subcortical thalamic neurons on more even footing with cortical neurons. These include making a spike-triggered single cortical neuron map in which multi-unit activity or LFP-triggered activity has been subtracted away. This would potentially allow the contributions of individual cortical neurons to be more easily seen.This is a great suggestion and we have already done preliminary studies using single-channel MUA spiking  and 2. WIn response to the reviewer’s suggestions that we subtract “a scaled version” of MUA based STM from single-unit STM, unfortunately the results appear largely as very noisy maps . This is due to the similarities between single-unit and MUA STMs before subtraction. However, we agree overall that this general direction could be pursued further in future work to determine whether the limit of the GCaMP temporal and spatial resolution allows for more nuanced single-unit STMs to be obtained by removing common baselines.See amended text from Results section:“We have also assessed other means of generating event triggered maps including MUA and LFP frequency bands. […] In contrast, in the case of GCaMP6 higher frequency components are closer to hemodynamic and other noise sources making analysis more challenging.”2) We thank the reviewer for highlighting these findings from Logothetis et al. As we did not record simultaneously from the hippocampus we cannot definitely comment on the relationship between thalamic spiking activity and the observation of net cortical inhibition with respect to hippocampal ripples in our experiments. However, the data presented in Logothetis et al. are remarkable and consistent with this interpretation and we now more clearly discuss our observations in this interesting context in our revised Discussion.See amended text in Discussion section:“The approach is probably most analogous to event-triggered MRI imaging from the standpoint of larger spatial scale . […] However, as we did not record simultaneously from hippocampus we cannot definitively comment on whether these observations necessarily correspond to hippocampal ripple events.”With respect to the specific comment of “the true level and time course” of activity, we have addressed this in greater detail in regard to the reviewer suggestion of implementing a running median subtraction in comment (3C).3) Several analysis choices make the findings difficult to interpret: (a) there is no correction for vascular effects despite analyses spanning several seconds surrounding the spike: it is surprising that no vascular responses are seen in STMs in the GFP control, please discuss. (b) the authors suggest using deconvolution of signals as a future direction, but this would seem to be highly useful to use in the present analyses in separating GCaMp6 dynamics from neural dynamics, given the emphasis, in part, on temporal resolution (relative to fMRI). Both points (a) and (b) are effectively addressed in a study that is in some ways quite similar, by Wekselblatt et al., J Neurophys June 2016 -- a paper that is not cited by the authors. In that paper, Wekselblatt et al. nicely show the use of stimulus-evoked widefield GCaMP6 mapping across an intermediate sized cranial window in mice, after deconvolution and removal of vascular signals.The reviewer notes that there is no correction for potential vascular effects despite the signals spanning several seconds around the spike and it is surprising that we do not see vascular responses in the spike-triggered maps from GFP controls. We have more thoroughly addressed this point in our response to the Essential Revisions (comment 2) and now report new data using a normalization procedure in a new supplemental figure . In our The reviewer suggests a temporal deconvolution for signals to improve time resolution. We have now performed such an analysis and report these results . While s(c) Another issue that is difficult to interpret is the normalization of GCaMP6 signal to a window of time prior to spike onset. Clearly this is throwing out a lot of useful information, and may distort much of the information that remains. An alternative approach might be to use a running median subtraction at each pixel, perhaps with removal of any slow drifts over long timescales, which would more effectively reveal what GCaMP6 activity is leading vs. lagging the spiking activity.The reviewer suggests different methods for averaging calcium activity frames, in particular a “running median” method. We previously employed two different methods including a “global signal regression” method in which the baseline fluorescence is the mean of the entire ~5 minute recording stack. We also employed a low-band pass filtering method where the entire image stack was filtered at 0.1Hz-6Hz. The STMs provided by these methods appeared to be largely similar to the sliding window methodology likely because averaging over 3sec, 5 minutes or low-band pass filtering yield similar components in the calcium signal.Slow drifts were very occasionally observed during recordings. However, in the initial manuscript, STA generated from random spike times, not carrying neuronal activity but still affected by slow drifts in the same manner, were used for correction  No discuss of the nature of the spiking activity is presented, yet burst firing  may also distort the STMs.We have now addressed the issue of the potential relationship of burst firing and STMs in our response to the Essential Revisions Comment #3.(e) The cortical delineation of areas is crude, and most secondary areas are not well delineated, making it difficult to assess whether any specific spatial resolution afforded by the technique actually yields insights at the level of specific higher cortical areas.The reviewer would like to see better delineation of secondary cortical areas. Unfortunately, using a bilateral imaging window implant, we do not have optical access to most secondary somatosensory areas. We have replaced the figure panel in Regarding spatial resolution, we have revised the Methods section to include acknowledgement of the spatial resolution of our imaging and references to our previous work from which these measurements are described in detail.See the amended text in Materials and methods:“In order to reduce file size and minimize the power of excitation light used, we typically bin camera pixels (8 × 8) thus producing a resolution of 68 µm/pixel. These imaging parameters have been used previously for voltage sensitive dye imaging  as well as anesthetized GCaMP3 imaging of spontaneous activity in mouse cortex  and awake GCaMP6 imaging in mouse cortex with chronic window .”(f): While it is interesting and useful to see that STM patterns become similar after averaging >128 or 256 trials , most ofWe have now addressed the issue of heterogeneity of STMs and the use of averaging in our response to the Essential Revisions Comment #3.4) Description of the choice of epochs included in "spontaneous activity" is unclear. The authors do not seem to use body-tracking data that they collect and describe in Methods in order to segregate epochs of true spontaneous activity. The "spontaneous activity" may currently include sensory-evoked activity , even though these behaviors were observed, as stated in "Methods: Multimodal recording in awake mice."We have now addressed the issue of the potential contribution of active behaviours in our response to the Essential Revisions Comment #4.5) Our results presented in See amended text in Results section:“This classification showed that ~80% cortical neurons were associated with a pure cortical excitation profile (pattern #1) and 20% triggered inhibition (pattern #2). […] We suggest future work with larger datasets and multiple cortical/subcortical areas could address the question of whether STMTD classification are a novel intrinsic single-cell property.”


Actinobacteria (20–66%), Chloroflexi (9–29%), and Firmicutes (7–42%) and an increase in the relative abundance of Actinobacteria with increasing soil nutrient content. The archaeal community reached up to 14% of the total soil microbial community and was dominated by the thaumarchaeal Soil Crenarchaeotic Group (43–99.8%), with a high fraction of sequences related to the ammonia-oxidizing genus Nitrosopshaera sp. Quantitative PCR targeting amoA genes encoding the alpha subunit of ammonia monooxygenase also revealed a high genetic potential for ammonia oxidation dominated by archaea . Abundances of archaeal 16S rRNA and amoA genes were positively correlated with soil nitrate, N and C contents. Nitrospira sp. was detected as the most abundant group of nitrite oxidizing bacteria. The specific geochemical conditions and particle transport dynamics at the granitic catena were found to affect soil microbial communities through clay and nutrient relocation along the hill slope, causing a shift to different, less diverse bacterial and archaeal communities at the footslope. Overall, our results suggest a strong effect of the savanna soils' nutrient scarcity on all microbial communities, resulting in a distinct community structure that differs markedly from nutrient-rich, temperate grasslands, along with a high relevance of archaeal ammonia oxidation in savanna soils.Savannas cover at least 13% of the global terrestrial surface and are often nutrient limited, especially by nitrogen. To gain a better understanding of their microbial diversity and the microbial nitrogen cycling in savanna soils, soil samples were collected along a granitic and a basaltic catena in Kruger National Park (South Africa) to characterize their bacterial and archaeal composition and the genetic potential for nitrification. Although the basaltic soils were on average 5 times more nutrient rich than the granitic soils, all investigated savanna soil samples showed typically low nutrient availabilities, i.e., up to 38 times lower soil N or C contents than temperate grasslands. Illumina MiSeq amplicon sequencing revealed a unique soil bacterial community dominated by  As the most common (sub-) tropic vegetation type, savannas cover over 13% of the global terrestrial surface and host 20% of the current human population  and Thaumarchaeota (AOA)  , but their ecological relevance remains unclear at this point  and a few Euryarchaeota make up the archaeal communities , South Africa, as a model environment. KNP is located in the northeastern part of South Africa and encompasses almost 2 million ha of subtropical deciduous savanna landscapes inhabited by intact herbivore and carnivore populations, ensuring integrity of most ecosystem processes. Geologically, the western half of KNP lies on Kaapval granite and metagranites while basalts (Karoo volcanics) underlie the eastern half  to identify to what extent microbial community structure of the KNP savanna soils differs from those usually found in temperate grassland soils, (ii) to assess the impact of the sites' contrasting bedrock material and resulting soil geochemistry and catena dynamics on the soil microbial communities and (iii) to evaluate the genetic potential for nitrification by targeting −1 and 44 kg ha−1), soil properties, landscape forms and vegetation  and a palatable grass layer. The basaltic catena, on the other hand, is characterized by red olivine-poor, nutrient-rich soils of higher clay content and lower water conductivity, thus leading to a spatially less well-differentiated catena type. On these soils, the vegetation consists of fine-leaved tree savanna  with a lush grass cover .The samples investigated in this study were collected along two semi-arid catenas with geologically different parent materials in South Africa's Kruger National Park  at different locations along the two catenas  and removal of the supernatant, i.e., most of the applied RNAlater solution.One replicate of each sample was stored at 4°C for chemical analyses and soil respiration measurements while the other three replicates were treated immediately with RNAlater  to prevent loss or fragmentation of nucleic acids and were then subsequently stored at 4°C for a few days. This resulted in 21 samples for molecular biological analysis, which were stored at −80°C after centrifugation , and specific respiration (qO2) were measured by substrate-induced respiration (SIR), i.e., the respiratory response of microorganisms to glucose addition . Cmic (μg C g−1) was calculated as 38 × MIRR (μl O2 g−1 soil dry weight h−1) according to Beck et al. (2 (μl O2μ g−1 Cmic h−1) was calculated as BAS/Cmic and eflects carbon use efficiency.Basal respiration (BAS), microbial biomass , bacterial amoA and archaeal amoA  genes. These genes were amplified from DNA extracts of the corresponding triplicate samples using HotStarTaq Master Mix . For the amplification of archaeal and bacterial amoA genes, primer pairs Arch-AmoAF/Arch-AmoAR . For this purpose, PCR products were generated in triplicate per DNA extract and all PCR products from PCR replicates and replicate soil samples per site were pooled. Plasmid DNA was purified using GeneJET Plasmid Miniprep Kit  and inserts were commercially sequenced .PCR products were checked by agarose gel electrophoresis and purified using the NucleoSpin Gel & PCR Clean-Up Kit  according to the manufacturer's instructions. Clone libraries were constructed from purified -NNN NNNNNNNTCCTACGGGNGGCWGCAG and reverse primer 785R 5′-NNN NNNNNNNTGACTACHVGGGTATCTAAKCC in 20 uL volume of 1 × MyTaq buffer containing 1.5 units MyTaq DNA polymerase (Bioline) and 2 μl of BioStabII PCR Enhancer (Sigma). For each sample, the forward and reverse primers had the same 10-nt barcode sequence. PCRs were carried out for 30 cycles using the following parameters: 2 min 96°C predenaturation; 96°C for 15 s, 50°C for 30 s, 70°C for 90 s. DNA concentration of amplicons of interest was determined by gelelectrophosesis. About 20 ng amplicon DNA of each sample were pooled for up to 48 samples carrying different barcodes. If needed PCRs showing low yields were further amplified for 5 cycles. The amplicon pools were purified with one volume AMPure XP beads (Agencourt) to remove primer dimer and other small mispriming products, followed by an additional purification on MinElute columns (Qiagen). About 100 ng of each purified ampliconpool DNA was used to construct Illumina libraries using the Ovation Rapid DR Multiplex System 1–96 (NuGEN). Illumina libraries were pooled and size selected by preparative gelelectrophoresis. Sequencing was done on an Illumina MiSeq using V3 chemistry (Illumina).Illumina MiSeq amplicon sequencing targeting bacterial and archaeal 16S rRNA genes was performed on all samples using the primer combinations Bakt_805R/Bakt_341F  search of sequences representative of each OTU. Phylogenetic trees including sequences representative of each OTU were constructed  in ARB based on the respective protein reference alignments.Sequences obtained from http://www.mothur.org/wiki/MiSeq_SOP; Kozich et al., Illumina MiSeq amplicon sequencing was performed for bacterial and archaeal 16S rRNA genes obtained from all soil samples. The software Mothur was used to analyze all obtained reads  using Maxima SYBR Green qPCR Mastermix . 16S rRNA genes were amplified using primer pairs Bac8Fmod/Bac338Rabc , a maximum estimate of gene abundances per g soil was calculated based on this quantification limit. Fractions of microorganisms harboring amoA genes within the total microbial population were estimated from respective qPCR results by using the following correction factors to account for the possibility of multiple gene copies per genome: 4.02 for the bacterial 16S rRNA gene and 1.63 for the archaeal 16S rRNA gene  and showed mostly low nutrient contents , along with the highest concentrations of ammonium  observed along the granitic catena and the lowest clay, nitrate, organic C and N contents across samples from both catenas (Table B = 6.2 ± 0.05) and exhibited on average five times higher soil N, C and nitrate contents than the granitic soils with the highest ammonium concentration again being detected at the mid-slope position, i.e., in this case 33.23 μg g−1 at BII. Nitrite concentrations were generally low at both catenas .The granitic savanna soils were dominated by sand-sized particles, were moderately acidic , while microbial biomass (Cmic) varied between the two catenas and between sampling sites along each catena, reaching a maximum of 398.66 μg Cmic g−1soil dw at the basaltic mid-slope location (BII) and a minimum of 68.82 μg Cmic g−1 soil dw above the granitic seep zone (GII). Carbon use efficiency (qO2) was also higher in the basaltic soils (mean qO2B = 0.0068 μl Om2 g−1 Cmic h−1) than in the granitic soils and especially low at GII with qO2GII = 0.0199 μl O2μg−1 Cmic h−1 , Chloroflexi (5–28%) and Firmicutes , appeared to harbor the highest phylum-level diversity, with e.g., Planctomycetes and Acidobacteria accounting for the highest read fraction across the whole transect at that location. The relative fraction of sequence reads affiliated with Actinobacteria increased along the granitic catena, reaching levels of around 50% at site GIII. Chloroflexi -associated reads, on the other hand, decreased in relative abundance along the granitic catena, while no clear trend could be observed for Firmicutes. The bacterial community composition at sites BI-III was very similar to the granitic downslope sites with even higher fractions of sequence reads affiliated with Actinobacteria (36–66% of sequence reads) and lower fractions of Chloroflexi (8–15%)  or Thermoleophilia (41%). Most of the Firmicutes-affiliated reads belonged to Bacilli (91%) and Clostridia (6%) and most of the Chloroflexi-affiliated reads were assigned to Ktedonobacteria (39%), group TK10 (20%) and JG37-AG-4 (12%). The majority of Acidobacteria reads belonged to the subgroups 1, 3, 4, and 6 or remained unclassified. On the whole, the classes Actinobacteria, Thermoleophilia and Bacilli made up the majority of the bacterial community at most of the sampling sites, with Ktedonobacteria being additionally abundant and almost exclusively detected at GI and GII , the woesearchaeal Rice Cluster V Group (RC-V) and euryarchaeal unclassified Thermoplasmatales also accounted for a high fraction of sequence reads in some samples . Notably, FSCG appeared most dominant in the granitic upslope soils, especially above the granitic catena's seep zone (GII). Reads belonging to RC-V were found in several samples and were also particularly abundant at site GII. Other groups with read frequencies higher than 1% in some samples were assigned to the Deep sea Hydrothermal Vent Euryarchaeota Group 6 (DHVE-6), the Rice Cluster III Group (RC-III) and different euryarchaeal methanogenic groups. The latter three of these groups were almost exclusively found above the seep zone (GII), where e.g., the methanogenic archaea together reached a maximum abundance of 2.7%. In summary, a clear variation of archaeal community structure was observed along the granitic catena, with more diverse archaeal communities occurring in the upslope soils above the seep zone . In contrast, the archaeal communities at the granitic and basaltic downslope positions  were largely dominated by Thaumarchaeota affiliated with AOA. Additionally, GII was the only site where considerable abundances of methanogenic archaea were detected and the site with highest abundances of RC-V, DHVE-6, RC-III and methanogen affiliated 16S rRNA reads.Archaeal 16S rRNA gene abundances varied around 3 × 10amoA gene abundances varied between 6.5 × 106 and 1.7 × 108 genes g−1 soil and outnumbered bacterial amoA genes by at least two orders of magnitude at almost all sampling locations. Furthermore, qPCR-based gene abundances suggested that AOA made up 1.4–6.9% of the total microbial community and 21–77% of the archaeal community. Abundances of bacterial amoA genes, on the other hand, were below the method's quantification limit (ca. 7 × 104 copies g−1 soil) in all samples except BII where 6 × 106 bacterial amoA genes g−1 soil were detected. Both archaeal 16S rRNA and amoA gene abundances increased along the granitic catena  and nitrite oxidizing bacteria (NOB) were investigated using functional gene-based approaches. Band patterns from an AOA-Nitrospira sp., which accounted for 0.1% of all obtained bacterial 16S rRNA reads across sites. The two clone libraries constructed for the Nitrospira sp.-derived nxrB gene resulted in a total of 16 OTUs (distance cutoff: 0.05 on nucleic acid level), which were affiliated with Nitrospira moscoviensis (identities: 89–93%) and several other Nitrospira-related sequences  the soil heterotrophic microbial community  Proteobacteria as the two dominant bacterial phyla in soils, often accompanied by Actinobacteria as another abundant group , which would be expected in the rhizosphere of Acacia sp. found in the catena's downslope areas but not below Combretum sp. and Terminalia sp. at the upper granitic catena  relative to bacterial amoA gene abundances (mostly ≤ 7 × 104 copies g−1 soil). To our knowledge, a predominance of archaea within the ammonia-oxidizing communities has not yet been described for savanna soils but is well known for various other soil environments  and to become active on short time scales under temporary wet, anoxic conditions  exhibited a particularly distinct geochemistry and microbiology - likely because soils were subjected to seasonally fluctuating redox conditions above the actual seep zone, especially at sampling time near the end of the local wet season. Soils from GII were the most acidic and nutrient poor, showed high ammonium concentrations and the lowest microbial carbon use efficiency. The CCA performed with environmental parameters and bacterial 16S rRNA gene-based OTU frequencies also showed the strong distinction of this location from all other sampling sites. However, the variation underlying this separation could not fully be accounted for by the five tested environmental variables, indicating that variation here might be driven by potentially other relevant environmental parameters, such as redox potential or temporal fluctuations in water saturation, which were not assessed in our study. At this “above seep” location, several distinct bacterial and archaeal groups were also detected in higher relative abundances than in soils from the other sampling locations. Actinobacteria, Chloroflexi, and Firmicutes in the soil bacterial communities, which differs strongly from more nutrient-rich, temperate grassland soils. The oligotrophic status of the investigated soils was further reflected by an exceptionally high fraction of archaea in the soil microbial communities, which were mostly dominated by ammonia-oxidizing thaumarchaeota closely related to Nitrososphaera sp. The observed high numerical predominance of ammonia-oxidizing archaea compared to ammonia-oxidizing bacteria pointed to an important role of archaea in savanna soil nitrogen cycling, most likely in combination with nitrite oxidation by Nitrospira-related NOB. The general effect of the special properties of the savanna soils on the soil microbial communities was further modulated by the influence of bedrock material, resulting in the occurrence of some ammonia and nitrite oxidizers restricted to soils of either the granitic or basaltic catena.Our results have clearly demonstrated that the nutrient-poor conditions in South African savanna soils are a strong driver of microbial community structure, resulting in a dominance of archaea and Rice Cluster V archaea above a seasonal seep zone. Overall, our results suggest a strong effect of the savanna soils' nutrient scarcity and seasonal water limitations on all investigated microbial communities, resulting in the presence of distinct bacterial communities which differ strongly from those found in temperate grassland soils.Along the granitic catena, specific geochemical conditions and particle transport dynamics were found to affect the soil microbial communities through clay and nutrient relocation along the hill slope, probably underlying a shift to different, less diverse bacterial and archaeal communities at the downslope locations. Additionally, seasonal heterogeneity in soil water regime along the granitic catena may have supported the local occurrence of methanogenic KK, ST, and MH designed the work. ST, SL, and KK carried out field sampling. ST and SL contributed substantially to the biogeochemical, transect-oriented interpretation of the results. SR performed all molecular work and wrote the first version of the manuscript. Analysis of sequence data was carried out by SR and MH. SC contributed data of microbial respiration and biomass. CL performed the analysis of archaeal sequence data sets. All authors contributed to the writing of the manuscript.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.


With increasing use of immunotherapy agents, pretreatment strategies for identifying responders and non-responders is useful for appropriate treatment assignment. We hypothesize that the local immune micro-environment of NSCLC is associated with patient outcomes and that these local immune features exhibit distinct radiologic characteristics discernible by quantitative imaging metrics. We assembled two cohorts of NSCLC patients treated with definitive surgical resection and extracted quantitative parameters from pretreatment CT imaging. The excised primary tumors were then quantified for percent tumor PDL1 expression and density of tumor-infiltrating lymphocyte (via CD3 count) utilizing immunohistochemistry and automated cell counting. Associating these pretreatment radiomics parameters with tumor immune parameters, we developed an immune pathology-informed model (IPIM) that separated patients into 4 clusters (designated A-D) utilizing 4 radiomics features. The IPIM designation was significantly associated with overall survival in both training  and validation  cohorts and immune pathology . Specifically, we identified a favorable outcome group characterized by low CT intensity and high heterogeneity that exhibited low PDL1 and high CD3 infiltration, suggestive of a favorable immune activated state. We have developed a NSCLC radiomics signature based on the immune micro-environment and patient outcomes. This manuscript demonstrates model creation and validation in independent cohorts. Indeed, anti-PD1 and anti-CTLA4 checkpoint inhibitors have led to responses in a proportion of NSCLC patients, but many patients do not respond8. Efforts are underway to identify predictors of response, yet most such efforts are limited to analyses of biopsy-based pathologic biomarkers or serum samples10. One rich source of biophysical data that has not been thoroughly investigated for this purpose is radiomics, defined as the quantification of imaging features from CT or other imaging modalities13. As a predictive marker, radiomics has several advantages over tissue-based biomarkers, including being noninvasive, easily used for serial monitoring, implemented clinically by using standard-of-care imaging, and acquiring data from the entire tumor.Immunotherapy has shown promise for the treatment of several types of cancer, including non-small cell lung cancer (NSCLC)16. However, several shortcomings have impeded the clinical utilization of radiomics, including the lack of a clear underlying biological rationale to explain the association between radiomics and outcomes in addition to the abstract mathematical nature of radiomics parameters17. Efforts thus far have identified associations between EGFR and KRAS mutations with radiomics features in NSCLC19. One of the most significant drivers of the local tumor environment, and correspondingly of patient outcomes in NSCLC, is the local inflammatory reaction21. Immune-related phenomena such as increased vascular permeability, cytokine release, lymphocyte infiltration, and fibrosis produce corresponding imaging correlates on CT24. Given emerging evidence suggesting that NSCLC is driven in substantial part by the local immune environment21, we hypothesized that patterns of enhancement, texture, shape, and morphology intrinsic to the local immune phenotype could be ascertained through interrogation of radiomics features. This retrospective study was devised to identify and validate image-derived prognostic signatures for NSCLC that reflect the local immune microenvironment and are prognostic for patient survival.Associations between radiomics and patient outcomes have been shown for NSCLCP = 0.005), adenocarcinoma/not otherwise specific (NOS) histology , and less common use of adjuvant therapy .Demographics for the training cohort n = 114) and validation cohort (n = 176) are presented in Table 14 and va2  had the highest OS rate at 5 yr (80%), and patients with immune-inhibited tumors (CD3loPDL1hi) had the worst OS rate at 5 yr (35%) (P = 0.04)  and % of tumor cells expressing PDL1 (to assess tumor-mediated immune suppression). In the training cohort, optimal cutoffs for both metrics were determined to maximize association with OS when partitioning this cohort into 4 immune pathology groups: PDL1 cutoff of 2% and a CD3 count cutoff of 1910 cells/mm2 Fig. . Represe04) Fig. . This as04) Fig. .Figure 1P = 0.002)  Fig. . This as02) Fig. . ConcordP < 0.05) and immune-pathology grouping (P < 0.05), 1 of which was entirely composed of highly reproducible features  generated 8 independent radiomics models that were associated with immune-pathology features and/or OS . These pathology characteristics are described for each cluster. Significant differences in OS were also observed among IPIM clusters (P = 0.01). Cluster D had a predominantly immune-activated phenotype, with high CD3 and low PDL1 expression . Again, pathology features of patients in Cluster D were most consistent with an immune-activated phenotype, with the lowest proportion of cells expressing PDL1 and the highest frequency of CD3+ cells , with patients in Cluster D once again having better 5-yr OS rates (86%) than those in Cluster A (55%), Cluster B (72%), and Cluster C (75%). In the validation set the association of Cluster D with better OS held on multivariate analysis  disease from the validation dataset (n = 111). That analysis revealed a significant association between IPIM Cluster D and improved OS . Given the immune-inhibitory function of PDL1 and the immune-activated state portended by increasing tumor infiltration by CD3+ cells, it is reasonable to assume that tumors with high CD3 infiltration and low PDL1 expression, which portend an immune-activated state, would be linked with the best patient outcomes  predominantly by using supervised analytical methods. The IPIM model presented here was identified among a selected subset of radiomics models that had been screened for associations with immune-pathology features and OS. We used two immune-pathology features to describe the immune microenvironment, CD3+ cell density and percent tumor cell PDL1 expression, to separate patients into 4 groups. This paradigm has been used previously for patients with melanoma16, discerning malignant versus benign lung nodules27, and, more recently, assessing NSCLC mutation status28. Efforts correlating biological phenomena with radiologic features in NSCLC have otherwise been generally limited. To our knowledge, the current study represents the first radiomics analysis to link the tumor immune microenvironment with survival. Notably, patients in this study had been treated in an era when immunotherapy was not used for NSCLC. Thus the observed differences in outcome were probably derived from the biological phenotype. We hypothesize that the differences in outcome noted in the IPIM subgroups will become more pronounced in the current era, given the increasing use of immunotherapy for this disease.Current reports of the use of radiomics for lung cancer have focused on 3 areas: describing patient outcomes31. It is therefore plausible that the IPIM classification, in conjunction with pathology, could be used to predict or monitor response to immunotherapy. Analysis investigating the predictive power of the IPIM classification in patients treated with checkpoint inhibitors is ongoing.The predominant biomarker to determine eligibility for PD1 inhibitors use is tumor PDL1 expression. However, pathology analysis alone is limited by the heterogeneous expression pattern of PD-L1 on tumor cells, which varies significantly due to changes in the utilized assay, IHC antibody, and specimen sizeAside from the inherent weaknesses associated with retrospective reviews, various strengths and weaknesses deserve to be specifically mentioned. This study was conducted at a single institution and used only CT scanners at that institution. To facilitate outside validation we have created a web interface  to encourage its application beyond this study and at other institutions. Further, patients varied in cancer stage and era of treatment, thus receiving a variety of adjuvant treatment regimens. To adjust for this, we conducted a sensitivity analysis in our validation dataset limiting inclusion to only stage I patients T1-2N0M0), which reaffirmed the results from the larger cohort . We hypothesize that this entirely noninvasive model can be used in the current era to further elucidate the prognostic utility of the local immune environment and can be enhanced to predict or monitor response to immunotherapy agents, a subject of ongoing investigation.Training and validation cohorts were created from two patient datasets that were temporally separated with respect to staining, processing, and quantification. Inclusion criteria were having received definitive surgery, diagnosis of non-metastatic disease, pathologically confirmed NSCLC, and lack of induction therapy. All patients had a pretreatment staging chest CT with contrast agent at our institution as part of the standard of care and had an adequate surgical pathology specimen for IHC staining. All methods were carried out in accordance with relevant guidelines and regulations. All analyses were approved by the appropriate Institutional Review Board at MD Anderson Cancer Center, with the requirement for consent waived given the retrospective design.2 of analyzed tissue). Percentage of tumor cells staining for PDL1 was quantified with the GENIE histology pattern recognition algorithm (Aperio) for automated identification of the tumor regions, under a pathologist’s supervision, via a membrane algorithm. Further details regarding staining technique are provided in the following references33.Four-micron-thick sequential histologic tumor sections were obtained from a representative formalin-fixed, paraffin-embedded tumor block and used for IHC analysis. IHC staining was done using an automated staining system  with antibodies against PDL1  and CD3 . Marker expression was detected with a Novocastra Bond Polymer Refine Detection kit (Leica Biosystems) with a diaminobenzidine reaction to detect antibody labeling and hematoxylin counterstaining. The slides were then scanned in an Aperio AT2 scanner (Leica Biosystems). CD3+ cells were counted by a pathologist using Aperio Image Toolbox analysis software  and expressed as cell density  into 4 previously established pathology groups based on T-cell infiltration and tumor PDL1 expression as follows: PD-L135. Radiomics features were extracted from contoured tumors by using IBEX  to contour a random set of 10 patients. Features exhibiting <3% deviation attributable to inter-user heterogeneity in both programs were considered “highly reproducible” and thereby given preference for radiomics model selection. The resultant Bland-Altman plots are reported in Supplementary Fig. Pretreatment chest CT scans with contrast agent were obtained at our institution and contoured by using 3D SlicerhiCD3hi, PDL1loTILlo, PDL1hiTILlo, PDL1loTILhi with likelihood-ratio tests obtained from log-linear multinomial regression25. Regression models estimated the relative odds of each cluster assignment given the observed expression levels of PDL1 and CD3. Six candidate signatures were selected as highly associated with immune pathology based on the training set. Thereafter, clusters from the selected feature sets were evaluated for association with OS in univariate analysis based on the log-rank test. To ensure that the inferred relationships represented independent lines of association from standard clinical knowledge, Cox proportional hazards regression was applied to adjust the radiomics estimators for the partials of effects of prognostic clinical factors and treatment factors: lesion size, N-status, histologic subtype, age at surgery, and whether adjuvant therapy was administered.All statistical analyses were conducted with R statistical software . The ConsensusClusterPlus package was utilized to identify radiomics clusters. In addition we utilized the nnet, gplots, survival, and ConsensusClusterPlus packages. To identify robust, reproducible signatures, we avoided supervised clustering based on patient outcomes. Inter-patient dissimilarity was computed by Manhattan distance, which measures the absolute distance between two vectors. Hierarchical cluster analysis was implemented based on Ward’s method with ranks 2–6, follow Z-transformation of all radiomics parameters. Candidate clustering schemes were then evaluated for association with individual immune-pathology markers based on Spearman’s rank correlation coefficient and tested for evidence of association with the resultant immune-pathology subtypes of PDL140. Consensus clustering was implemented based on the hierarchical clustering algorithm with Manhattan distance function using rank size fixed at the number of clusters-levels for the considered signature. All tests were two-sided where applicable and considered significant when P ≤ 0.05.Model validation was conducted in an independent cohort. Similar to the pathology model, cutpoints identified in the training cohort were then applied to the validation cohort. For each of the 6 selected signatures, radiomics cluster assignments were obtained independently for each patient in the validation set by evaluating their extent of pairwise similarity with each patient in the training set. Each validation patient was assigned to one training cluster based on the k-nearest-neighbor algorithm applied to similarity measures obtained from consensus clustering using k = 5Supplementary Information


EDN1 rs5370 and EDNRA rs5335 gene polymorphisms and the risk of large artery stroke (LAS) in a Ukrainian population was conducted. 200 LAS patients and 200 unrelated controls were enrolled in a case-control study. The polymerase chain reaction-restriction fragment length polymorphism method (PCR-RFLP) was used for SNP genotyping. Our results revealed that EDN1 rs5370 polymorphism was associated with LAS development both before and after adjustment for atherosclerosis risk factors . The risk for a LAS incident in rs5370-T allele carriers was 1.6 times higher  than in subjects with the GG genotype. No link between EDNRA rs5335 and LAS risk in a Ukrainian population was found. The present study indicated that EDN1 rs5370, but not EDNRA rs5335, can be the strong genetic predictor for LAS development in a Ukrainian population.There are a lot of convincing evidences about the involvement of endothelin pathway proteins in the pathogenesis of atherosclerosis and its fatal complications. In this study, the analysis of a possible association between  As it is well known, endothelial dysfunction plays an important role in the development of common cardiovascular diseases and their complications . One of EDN1) and its receptor (EDNRA and EDNRB) genes and development of arterial hypertension (AH) [EDN1, EDNRA, and EDNRB genetic polymorphisms on ischemic stroke (IS) development. Zhang and Sui showed that rs5370-T allele (EDN1 gene) increased the IS incidence risk in Northern Han men, whereas the rs5335-CC genotype (EDNRA gene) had a protective effect in the same population [EDN1 rs5370 polymorphism and high risk for IS only among Japanese women [In recent years, a wide range of case-control studies to test the association between various single nucleotide polymorphisms (SNPs) of the ET-1 (ion (AH) , 6, pulmion (AH) , myocardion (AH) , diabetiion (AH)  and nephion (AH) , metabolion (AH) , and hemion (AH)  have beepulation . Yamagucse women , whereasse women  and Englse women  populatiEDN1 rs5370 and EDNRA rs5335 polymorphisms and large artery stroke (LAS) in representatives of the Ukrainian population.The aim of the present case-control study was to investigate the possible association between Venous blood of 200 unrelated Caucasians (Ukrainians) with LAS  and 200 control subjects  was used for the study. Each stroke patient had been under dispensary observation in the 5th Sumy Clinical Hospital since April 2009 to December 2017. Computed tomography and (or) magnetic resonance imaging investigations of the head as well as electrocardiographic, biochemical, and coagulation tests and carotid ultrasonography were used for final LAS diagnosis establishment. The pathogenic variant of IS was determined according to the TOAST criteria [Only participants without the history of IS or other acute cerebrovascular pathologies, myocardial infarction, and other atherosclerosis complications were enrolled to the control group. Subjects of the comparison groups were divided into subgroups defined by sex and the presence or absence of AH . The study protocol complied with the Declaration of Helsinki and was approved by the Ethic Committee of the Medical Institute of Sumy State University (number 2/02.17.09). An appropriate written informed consent was obtained from all individuals.-restriction fragment length polymorphism analysis (PCR-RFLP) was used for genotyping EDN1 rs5370 and EDNRA rs5335 SNPs. The reaction mixture for PCR  included 2 mM MgSO4, 0.2 mM dNTPs , 5 μL 5 × PCR buffer, 1 U Taq DNA polymerase , and 75–100 ng DNA. The nucleotide structure of the primers and PCR conditions, which were used for each polymorphism investigation, are shown in Genomic DNA was isolated from peripheral leukocytes using GeneJET Whole Blood Genomic DNA Purification Mini Kit . Polymerase chain reactionСас81  was used for restriction analysis of EDN1 rs5370 polymorphism (incubation at 37°C for 17 h). The presence of guanine at the 5665th position of the EDN1 gene led to the cleavage of the amplicon (262 bp) by Cac81 into two parts of 189 and 73 bp. In the case of guanine to thymine replacement, we had only one 262 bp fragment due to the loss of the Cac81 catalytic site (EDNRA rs5335 SNP required using 3 U of NmuCI (Tsp45I)  (incubation at 37°C for 19 h). The presence of cytosine at the 70th position of the EDNRA 3′-untranslated region (3′-UTR) allowed NmuCI to cut the primary amplicon (174 bp) into two fragments of 116 and 58 bp. Cytosine to guanine substitution resulted in preventing the restriction and preservation of the original 174 bp fragment  method was performed. Statistical power analysis was done using Quanto. Hardy-Weinberg equilibrium testing was carried out using Online Encyclopedia for Genetic Epidemiology Studies (http://www.oege.org/software/hardy-weinberg.html). Chi square (χ2) test was used to compare the frequency of EDN1 rs5370 and EDNRA rs5335 alleles and genotypes as well as other categorical variables between the control and case groups. An odds ratio (OR) and 95% confidence interval (CI) were obtained from logistic regression for dominant, recessive, and additive models of inheritance. Multivariable logistic regression was used to exclude the effect of other atherosclerosis risk factors including sex, age, BMI, AH, type 2 diabetes mellitus (T2DM), and smoking status. All statistical tests were based on a two-tailed probability; a value of P < 0.05 was considered as significant.The Statistical Package for Social Science software  was used for most statistical analyses. Continuous variables are presented as the mean ± SD ; categorical variables are presented as absolute number and percentage value. Two-tailed Student's EDN1 rs5370 and EDNRA rs5335 polymorphic sites, web available consensus classifiers PredictSNP2 [EDN1 5 exon on protein function PredictSNP was used [EDNRA 3′-UTR.In order to uncover the functional effects of dictSNP2  and SNPidictSNP2 . Herewitwas used . We alsowas used . Online was used  was usedThe general characteristics of the study groups are summarized in EDN1 rs5370 and EDNRA rs5335 alleles and genotypes in comparison groups is shown in PHWE > 0.05). The frequency of EDN1 rs5370 genotypes and alleles in LAS patients significantly differed from the control group , while the distribution of EDNRA rs5335 genotypes and alleles was similar between case and control individuals . Statistical power analysis indicated that the rs5370 locus had strong power . At the same time, rs5335 SNP had poor power .The distribution of EDN1 rs5370 and stroke was revealed under dominant , recessive , and additive  models of inheritance. After adjusting for covariates of age, sex, BMI, AH, T2DM, and smoking status, genotypic association of rs5370 SNP remained under dominant , recessive , and additive  models. Logistic regression analysis for EDNRA rs5335 did not show any significant link with LAS development neither before nor after adjustment for atherosclerosis risk factors (P > 0.05).The results of two investigated SNP genotypes' association with LAS are presented in Pc = 0.021; ORc = 2.090, 95% CI = 1.119–3.903) and additive  models, as well as in adjusted dominant  and additive  models. EDNRA rs5335 SNP was not associated with stroke development in the female subgroup (P > 0.05). In male subjects, association of rs5370-TT genotype was revealed regardless of adjustment under recessive  and additive models . The significant link between rs5335 polymorphism and LAS development in the mentioned subgroup was absent (P > 0.05).The analysis of rs5370 and rs5335 genotypic association with LAS risk in female and male subjects is presented in EDN1 and EDNRA gene polymorphisms and ischemic stroke development in patients with and without AH (P > 0.05). In the hypertensive cohort, the minor T allele for the rs5370 locus was found to be significantly more prevalent in stroke patients. Before adjusting for covariates, positive association was revealed under dominant , recessive , and additive  models. After adjusting for the covariates, a significant link between EDN1 rs5370 and LAS remained under dominant , recessive , and additive  models.Due to influential role of the endothelin pathway in hypertension development, we also investigated the association between thout AH . In nonhEDN1 rs5370 genotypes. Using the ANOVA test, significant difference was found for diastolic  BP. Nevertheless, Bonferroni post hoc test revealed no significant difference between patients with different genotypes . Moreover, FDR multiple adjustment revealed that none of the parameters are associated with rs5370 genotypes. No link between EDNRA rs5335 genotypes and BMI, BP indices, coagulogram parameters, fasting glucose, and blood plasma lipid profile in stroke patients was found (as found .EDN1 rs5370 by the SNPinfo tool showed that the mentioned polymorphic locus might be located in splicing regulatory sequences recognized by exonic splicing enhancers or exonic splicing silencers (score—2.56). SpliceAId2 tool demonstrated that rs5370 lies between recognized sites for SFRS9 and hnRNP H1 splicing factors, but this SNP has no influence on their structure. Finally, prediction analysis by PredictSNP and PredictSNP2 allowed classifying EDN1 rs5370 (Lys198Asn mutation) as neutral ; MAPP—neutral with 68% EA; PhD-SNP—neutral with 78% EA; PolyPhen1—neutral with 67% EA; PolyPhen2—neutral with 61% EA; SIFT—neutral with 67% EA; SNAP—neutral with 50% EA; PredictSNP2—neutral with 89% EA; CADD—neutral with 90%; DANN—neutral with 73% EA; FATHMM—neutral with 84% EA; and FunSeq2—deleterious with 62% EA).The bioinformatical analysis of EDNRA rs5335 by the SNPinfo tool demonstrated that this SNP is possibly located in hsa-miR-27a-3p and hsa-miR-27b-3p binding sites (score—153.0). Analysis using miRDB confirmed that the EDNRA gene is in the list of mentioned miRNA targets (target score—50). However, PredictSNP2 results classified rs5335 mutation as neutral .Prediction analysis of EDN1 gene, which in turn leads to replacement of lysine by asparagine in the 198th position of the preproendothelin-1 molecule. Several studies have shown that endothelin-1 blood plasma concentration in T (Asn) allele carriers is higher than in subjects with GG (Lys/Lys) genotype [The essence of rs5370 polymorphism is the replacement of guanine by thymine at the 5665th position (5 exon) of the genotype , 25. Congenotype . In addiEDNRA gene and leads to cytosine/guanine conversion at position 61,772. The functional studies of this SNP do not exist, while several clinical studies have demonstrated the association of this locus with increased risk of AH development [EDN1 3′-UTR [EDNRA expression. Future functional analysis to confirm these results is required.The polymorphic site rs5335 is located within the 3′-UTR of the elopment , 28 and elopment . On the elopment . On the 1 3′-UTR . In ordeEDN1 gene) and rs5335 (EDNRA gene) polymorphisms with LAS showed that in a Ukrainian population, only the rs5370 locus is associated with the development of the mentioned disease. Regardless of adjustment for other atherosclerosis risk factors, it was found that the risk of ischemic stroke development in individuals with GT and TT genotypes is higher than in GG genotype carriers. However, a similar study performed by Aslan et al. among the Turkish population did not show any correlation between EDN1 rs5370 and rs10478694 polymorphisms and ischemic cerebrovascular disease [EDN1 (rs5370), EDNRA (−231G>A and +1222C>T), and EDNRB (G57S and 277L) gene polymorphisms and lacunar infarction development among English patients as well [The results obtained in the present study about the link of rs5370 ( disease . Herewit as well . The autEDN1), but not rs5335 (EDNRA) polymorphism, is associated with an increased risk of LAS both among women (under dominant and additive models) and men (under recessive and additive models). Such data were consistent with results obtained by Yamaguchi et al. [EDN1 rs5370 is related to ACI development susceptibility among women (under dominant and additive models). In the men's subgroup, the link with ischemic stroke was revealed for the EDNRA −231A>G locus (under the recessive model). At the same time, Zhang and Sui did not reveal an association between EDN1 rs5370 and EDNRA rs5335 polymorphic sites with ischemic stroke development among women of the Chinese Han population [EDN1 (rs1800542 and rs10478723) and EDNRB (rs4885493 and rs10507875) SNPs and increased risk of ischemic stroke development in Caucasian but not in African-American women [The analysis performed in our work among subjects of different sexes has showed that rs5370 (i et al. , who asspulation . They shan women .The issue of sexual difference in the endothelin system activity is one of the key topics of the cardiovascular and urinary system physiology and pathology . HoweverEDN1 rs5370 locus with increased risk of AH development, as well as with different parameters of blood pressure among Australian patients with ischemic heart disease, was not found [To date, there are number of studies about the association between endothelin system gene polymorphisms and risk of AH and pulmonary hypertension, as well as BP indices , 34–36. ot found .EDN1 and EDNRA mRNA level and ET-1 concentration in the blood plasma. Therefore, future case-control studies involving more patients and functional studies of endothelin pathway polymorphisms effects are required.A significant limitation of our study is the relatively small number of patients enrolled into the case and control groups. Therefore, some associations between rs5370 and rs5335 SNPs and the risk of LAS development, indices of blood pressure, blood plasma lipoprotein level, and coagulation parameters might have been missed due to a small statistical power. Another limitation is the investigation of the link between SNPs and phenotype without an assessment of their effects on the EDN1 rs5370 polymorphism is related to increased risk of LAS development regardless of other atherosclerosis risk factors. No link between EDNRA rs5335 and risk of LAS in a Ukrainian population was found. At present, a small number of case-control studies about the role of rs5370 and rs5335 SNPs in ischemic stroke development have been performed. Increasing the number of such studies with subsequent meta-analysis is necessary in order to draw a firm conclusion about the association between the mentioned polymorphisms and risk of ischemic stroke.In conclusion, this is the first evidence about the association between endothelin system genetic polymorphisms and LAS development in a Ukrainian population. Our data demonstrated that


Despite significant advances in current understanding of mechanisms of pathogenesis in Alzheimer’s disease (AD), attempts at drug development based on those discoveries have failed to translate into effective, disease-modifying therapies. AD is a complex and multifactorial disease comprising a range of aberrant cellular/molecular processes taking part in different cell types and brain regions. As a consequence, therapeutics for AD should be able to block or compensate multiple abnormal pathological events. Here, we examine recent evidence that inhibition of protein tyrosine phosphatase 1B (PTP1B) may represent a promising strategy to combat a variety of AD-related detrimental processes. Besides its well described role as a negative regulator of insulin and leptin signaling, PTB1B recently emerged as a modulator of various other processes in the central nervous system (CNS) that are also implicated in AD. These include signaling pathways germane to learning and memory, regulation of synapse dynamics, endoplasmic reticulum (ER) stress and microglia-mediated neuroinflammation. We propose that PTP1B inhibition may represent an attractive and yet unexplored therapeutic approach to correct aberrant signaling pathways linked to AD. There are currently no disease-modifying therapies for Alzheimer’s disease (AD), and treatments offer limited, temporary improvement in quality of life , neurotoxins that trigger synapse failure and lead to cognitive impairment , many of which therapeutically relevant for AD. Increased PTP1B activity is associated with defective neuronal insulin and leptin signaling  are important toxic mechanisms in AD , a form of activity-dependent synaptic plasticity thought to underlie learning and memory  is essential for stabilization of mushroom spines in hippocampal neurons  represents an additional obstacle drugs need to overcome to reach the CNS. Fortunately, however, significant advances have been achieved in developing effective PTP1B inhibitors with potential for clinical use. For example, an important recent study provided compelling evidence that potent and selective PTP1B inhibitors administered peripherally  inhibit PTP1B activity in the brain , Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ), National Institute for Translational Neuroscience (to FGF and STF) and Canadian Institutes of Health Research . MNNV is a former postdoctoral fellow of CNPq and a current fellow of FAPERJ. Studies on PTP1B inhibition as a therapy to Alzheimer’s disesase are funded by the International Society for Neurochemistry (ISN) Committee for Aid and Education in Neurosciences (CAEN) Career Interruption, Re-entry Grant (to MNNV). NMLS is a pre-doctoral fellow of CNPq.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.


The potential use of carbon nanotubes (CNTs) in gene therapy as delivery systems for nucleic acids has been recently recognized. Here, we describe that metallic versus semiconducting single-wall CNTs can produce significant differences in transfection rate and cellular distribution of siRNA in murine PAM212 keratinocytes.The results of cell interaction studies, coupled with supportive computational simulations and ultrastructural studies revealed that the use of metallic single wall CNTs resulted in siRNA delivery into both the cytoplasm and nucleus of keratinocytes, whereas semiconducting CNTs resulted in delivery only to the cytoplasm.Using enriched fractions of metallic or semiconducting CNTs for siRNA complex preparation may provide specific subcellular targeting advantages. Carbon nanotubes are a novel class of nanobuilding blocks extensively investigated as delivery systems for therapeutic RNAi to silence gene expression in the cell cytoplasm and nucleus. It was previously shown that the delivery properties of single wall carbon nanotubes (SWNTs) are influenced by their varied physicochemical characteristics, however, the effect of chirality and electronic properties of SWNTs have not been studied with respect to their role in cellular transfection. To the best of our knowledge, this is the first study that shows using metallic or semiconducting SWNTs for siRNA complex preparation may provide specific subcellular targeting advantages. Gene silencing by siRNA is a powerful approach for the treatment of many diseases, including many types of cancer, neurodegenerative, metabolic disorders and infectious diseases ,2. siRNAin vitro is still under investigation, there is mounting evidence that they are taken up into cells not only through endocytosis [Many of the challenges in achieving maximum RNAi are related to delivery issues, such as siRNA transport across the cellular membrane and/or translocation into the cytoplasm or nucleus following endocytotic uptake. Carbon nanotubes (CNTs) are a novel class of nanobuilding blocks extensively investigated as pharmaceutical delivery systems and may be useful as siRNA transfection agents . While aocytosis ,14, but ocytosis . This biocytosis ,20.et al. [et al. [et al. [et al. [The majority of studies indicate cytoplasmic localization of CNTs ,15,21–34 [et al. , fluores [et al.  and Port [et al. ,39 reporThe delivery properties of CNTs are influenced by their varied physicochemical characteristics. Studies have demonstrated that the nature , length, diameter and purity all play a role in CNT entry into cells ,41, whilThe objective of the research described in this manuscript was to determine whether siRNA delivery by SWNTs is associated with specificity with respect to intracellular localization and whether chirality influences cytoplasmic versus nuclear accumulation. Here, we describe the results of cell interaction studies, coupled with supportive computational simulations and ultrastructural studies that demonstrate the distinct cellular distribution behavior of metallic versus semiconducting SWNTs during cellular transfection, and a potential correlation with the binding of siRNA to SWNTs in the complex.ex = 557 nm/λem = 570 nm) was obtained from Dharmacon/Thermo Scientific . Nanotube dispersions in 1,2-dichlorobenzene [g for 15 min) were characterized by UV-Vis-NIR spectral scans between 200–1400 nm , Raman spectroscopy [N,N-bis-α,ω-alkanediammonium surfactant family was synthesized as previously described [Puretubes, Isonanotubes-M  and Isonanotubes-S  SWNTs of similar lengths were purchased as surfactant-eliminated powders from NanoIntegris Inc.  and further characterized . siGLO Lobenzene  and in 0troscopy  . Spectra were taken from three separate regions of the powder sample and overall average spectra were generated. Chiral species in the SWNT preparations were determined from the radial breathing mode frequency peaks (ωRBM) (100–350 cm-1) as previously described [CNTs were characterized in their dry state using a Senterra Dispersive Raman Spectrometer , with a 532 nm Nd:YAg laser at room temperature. The laser beam was focused onto the sample with a 20× objective and data were collected from 70 to 3700 cmBM) 100–3 cm-1 as escribed .Gemini 12–3–12 surfactant modified SWNTs (G-SWNTs) were prepared by sonication of 0.01 mg/ml SWNT in 0.1% (w/v) surfactant at room temperature using the combination of cuphorn closed vessel sonication  for 1 h and bath sonication for 6 h as previously described . One dosζ potential measurements were performed using laser Doppler micro-electrophoresis with Zetasizer Nano ZS Model ZEN3600 . The samples were analyzed in folded capillary DTS1060/DTS1061 cells using the Smoluchowski approximation model with Zetasizer software 7.10.6 cells/dish in a final volume of 3 ml MEM/EBSS  and heat inactivated FBS . Cells were then incubated at 37°C, in 5% CO2 overnight to allow attachment to the dish prior to treatment with SWNT complexes. When the cells reached 40–65% confluency, they were treated with the following SWNT complex formulations (100 µl per well): G-Puretubes-siRNA; G-IsoM-siRNA; and G-IsoS-siRNA. Once each SWNT complex was applied, the uptake of siRNA was determined at 1, 8 and 24 h time points, using an LSM 710 confocal microscope  and at each time point counterstained with calcein AM viability dye (Life technologies). DRAQ5  nuclear stain was used at the 24 h time point only.Murine PAM212 keratinocytes  were subcultured into 50 mm glass bottom Petri-dishes  to an initial total of approximately 1 × 106 cells/well) were cultured into 6-well plates in a final volume of 2 ml MEM/EBSS complete media overnight prior to treatment with SWNT complexes. The day after, cells were treated with 100 μl of G-IsoM-siRNA, G-IsoS-siRNA complexes and the nuclear uptake of siRNA was evaluated after 24 h incubation at 37°C and 5% CO2. At the end of incubation, cells were trypsinized and centrifuged at 200 × g for 5 min and then washed once with phosphate buffer saline (PBS). Cells were then resuspended in 1 ml of PBS and stained with 5 µg/ml Hoechst 33342  nuclear stain for 15 min. The cells were then washed with PBS and fixed in 100 µl formaldehyde fixation medium (Life Technologies). In total, 10,000 events were collected for all samples using the imaging flow cytometer; Cy3 was excited at 405 nm in channel 3 (560–595 nm) Hoechst 33342 in channel 7 (430–505 nm) and brightfield was emitted in channel 1. Single color controls were run for Cy3 and Hoechst 33342 to correct for spectral cross-talk within the multispectral experimental data. A compensation matrix was derived using the single color controls that were acquired under the identical experimental conditions. To detect siRNA nuclear colocalization, cell populations were hierarchically gated for single cells that were in focus and were positive for both Cy3 and Hoechst 33342 DNA staining. Post-acquisition spectral compensation and data analysis was performed using the IDEAS® image analysis software package (Amnis Corp.). Images were analyzed for the degree of colocalization using the IDEAS™ similarity bright detail (SBD) feature. SBD of the Cy3/Hoechst 33342 images was calculated and images with median nuclear localization score higher than 1 were considered positive for nuclear localization.For imaging flow cytometry analysis using the ImageStream Mark II imaging flow cytometer , PAM212 keratinocytes (1 × 105/ml) were resuspended in MEM/EBSS basic media and treated with siRNA-SWNT complexes (100 μl dose/well) in glass bottom 24-well plates (MatTek Corp.). After 16 h incubation at 37°C, the translocation of siRNA to purified nuclei was evaluated by confocal microscopy. Stacks of images consisting of 25–40 slices were collected from nuclei and deconvolved with Huygens Pro software . To estimate the colocalization between siRNA and nuclei, a minimum of five image stacks were evaluated using Huygens Pro software for Pearson's correlation coefficient (PCC) for each channel.Nuclei of PAM212 keratinocytes were isolated using the nuclear isolation kit Nuclei EZ Prep (Sigma-Aldrich) according to the manufacturer's instructions. The purity and integrity of isolated nuclei were confirmed by light microscopy following trypan blue staining. The isolation procedure yielded intact nuclei of at least 85% purity. Isolated nuclei  and left on for 30 s. The excess sample was drained off with filter paper and the grid dried. To remove excess surfactant matrix surrounding the nanotubes, the grids were washed by applying seven consecutive ultrapure water droplets onto the grid, draining off with filter paper. The nanostructures in the samples were examined with a FEI Titan 80–300 high-resolution (point-to-point resolution 2Å) transmission electron microscope (HRTEM)  equipped with a CEOS hexapole image Cs corrector and a Gatan Ultrascan CCD camera at the Canadian Centre for Electron Microscopy at McMaster University . The accelerating voltage was 80 kV. The illumination background on the images was corrected by calculating a local background of the micrograph using a 20 × 20 pixel real space kernel. This background was subtracted from the original micrograph.The secondary and tertiary structure of siRNA was modeled using the software package Assemble . SecondaStatistical analysis of the colocalization data was carried out using GraphPad Prism software . One way ANOVA test followed by Dunnet post hoc test was used for the analysis between different group experiments. A p-value of less than 0.05 was considered statistically significant.To develop siRNA-SWNT complexes we used commercially available nanotubes without further purification. Puretubes contain a mixture of chiral species, while the other two (IsoM and IsoS) SWNTs contain purified fractions of metallic or semiconducting nanotubes, respectively ; Table 1Following the incubation of G-SWNT-siRNA complexes with PAM212 keratinocytes, Puretubes complexes demonstrated significant differences in both the rate of transfection and the overall pattern of cytoplasmic and nuclear siRNA distribution . BindingNo treatment samples showed green fluorescence due to the calcein viability stain A and no In order to elucidate whether cytoplasmic factors were involved in the delivery of G-SWNT-siRNA complexes to the nucleus, the degree of nuclear siRNA colocalization was also assessed in purified nuclei after 24 h incubation with SWNT complexes . G-siRNAThe experimentally observed differences in cellular siRNA distribution led us to use complementary techniques to better understand siRNA interactions induced by the electronic structure of SWNTs and the possible role it may play on intracellular fate. Initial computer simulations examining bare SWNTs and their interactions with siRNA were in agreement with previous computational and experimental results that demonstrated CNT-siRNA interactions were induced through pi-stacking, resulting in decreased binding to metallic CNTs as a result of lower surface charge ,57. We oHigh-resolution electron microscopic observations of G-SWNT and G-SWNT-siRNA complexes further confirmed the data from the modeling experiments. The association of gemini surfactants and siRNA with IsoM and IsoS SWNTs is illustrated in significant morphological detail in Previous reports of siRNA delivery into cells using CNTs have typically employed chemically modified SWNTs ,26,31,40Based on experimental and computational modeling results, it is evident that binding of siRNA to metallic or semiconducting SWNTs differs as a result of their underlying electronic properties. Generally, siRNA may interact with SWNTs directly even if coated with gemini surfactant or there is a combination of interactions involving the electrostatic binding with the two cationic headgroups of the gemini surfactant already bound to the nanotube surface through its alkyl chain, similarly to reports on other surfactants and phospholipids ,60 and bUsing enriched fractions of metallic or semiconducting SWNTs for siRNA complex preparation may provide specific subcellular targeting advantages. Here, we have demonstrated that metallic SWNT complexes rapidly, within 1 h, deliver siRNA into keratinocytes and are capable of delivering siRNA into the nucleus, whereas semiconducting SWNTs transport siRNA slowly and to a more limited extent and only to the cytoplasm. These observations suggest that the electronic properties of IsoM SWNTs plays a significant role in siRNA delivery into the nucleus. While the underlying molecular mechanisms associated with this translocation process still need to be determined, it is apparent that this selectivity may provide advantages in the future development of nonviral gene delivery systems.Significant progresses have been made in the development of efficient siRNA delivery in non-viral systems, such as cationic lipids and polymers. However, a major problem with these approaches is the off-target effects of siRNA that has to be administered for efficient gene silencing. siRNA conjugation to antibodies or aptamers is a common approach for cell-specific targeted delivery. However, the development of delivery systems for siRNA to specific subcellular compartments such as the cytoplasm, nucleus, lysosome or mitochondria is still in its infancy. Based on what we have observed for CNTs, tuning the physicochemical properties of nanomaterials could be considered as an approach for developing intelligent delivery systems capable not only of cell-specific delivery but also targeting specific subcellular compartments, in particular nucleus, which is the critical step in gene therapy.Carbon nanotubes (CNTs) are a novel class of nanobuilding blocks extensively investigated as pharmaceutical delivery systems and may be useful as siRNA transfection agents.The objective of this research was to determine whether siRNA delivery by single wall carbon nanotubes (SWNTs) is associated with specificity with respect to intracellular localization and whether chirality influences cytoplasmic versus nuclear accumulation.The study presents confocal laser scanning microscopic imaging of purified fractions of metallic and semiconducting SWNT – cell interactions, supportive computational simulations and ultrastructural studies that demonstrate the distinct cellular distribution behavior of metallic versus semiconducting SWNTs during cellular transfection and a potential correlation with the binding of siRNA to SWNTs in the complex.Metallic SWNT (Isonanotubes M) complexes rapidly, within 1 h, deliver siRNA into keratinocytes and are capable of delivering siRNA into the nucleus, whereas semiconducting SWNTs transport siRNA slowly and to a more limited extent and only to the cytoplasm. These observations suggest that the electronic properties of IsoM SWNTs play a significant role in siRNA delivery into the nucleus.Tuning the physicochemical properties of nanomaterials is an important strategy for developing intelligent delivery systems capable of not only cell-specific delivery but also targeting specific subcellular compartments, in particular nucleus, which is critical in nucleic acid delivery.