Staphylococcus aureus (P = .024) when applied to nonwetted hands and showed no difference in skin barrier function compared with the reference soaps (P = .736).A non-antimicrobial soap was benchmarked against 2 reference soaps for microbial removal and skin compatibility, key factors in soap effectiveness and usage. The non-antimicrobial test soap removed more  The clinical effectiveness of hand hygiene programs is dependent on the complex relationship between multiple factors including hand hygiene products, education programs, hand hygiene monitoring and feedback practices, and an institutional safety climate , 2. For The microbial removal by non-antimicrobial soaps has been reported, but broad conclusions are difficult to make due to methodological, organism, and soap variation between studies . Skin coN,N′-disuccinic acid and removal of methylchloroisothiazolinone and methylisothiazolinone.Three commercially available non-antimicrobial soaps manufactured by GOJO Industries were tested in this study: (1) a base soap—Reference Soap A -7 glyceryl cocoate, polyquaternium-39, methylchloroisothiazolinone, methylisothiazolinone; (2) Reference Soap B, a modification of the base soap for skin health through increased glycerin and additions of PEG-8 and sodium pyroglutamic acid (PCA); and (3) Test Soap, a modification of the base soap for skin health and microbe removal through increased glycerin, addition of PEG-8, sodium PCA, ethyl alcohol, and trisodium ethylenediamine-Staphylococcus aureus ATCC 6538, a relevant healthcare pathogen, in 2 randomized, crossover studies using ASTM E2755-15 ) log10 colony-forming units (CFU)/hand. After applying soap to nonwetted hands, the Test Soap achieved a 1.46 (±0.36 SD) log10 reduction, which was statistically greater than the 1.12 (±0.32 SD) log10 reduction achieved by Reference Soap A (P = .024). In the second study, participants had an average baseline recovery of 8.80 (±0.32 SD) log10 CFU/hand. After soap application to prewetted skin, there was not a statistical difference in the log10 reduction of S aureus between the Test Soap (1.07 ± 0.19 SD) and Reference Soap A (0.97 ± 0.33 SD) (P = .356).In the first microbial removal study, subjects had an average P = .433 or Reference Soap B, P = 1.000) . Compared to controls when applied to nonwetted skin, the Test Soap showed a statistical difference  in skin barrier function versus 8% sodium lauryl sulfate applied to prewetted skin (positive control) and no statistical difference versus untreated skin (negative control) .In the skin compatibility study, comparison between soap application technique—prewetted and nonwetted skin—did not result in a statistical difference in barrier function for either soap  . There wS aureus in 15 seconds (data not shown). The Test Soap removed numerically more bacteria than the Reference Soap A when applied to prewetted skin, but this was not statistically significant. When applied to nonwetted skin, the soaps tested demonstrated significantly different microbial removal results. Because it has been reported that approximately half of users apply soaps to nonwetted skin [This is the first study to characterize a non-antimicrobial soap on multiple factors that drive performance and usage—microbial removal and skin compatibility. To reduce the transmission of pathogens soaps must reduce, through removal or biocidal action, microbial hand contamination. It was confirmed through in vitro suspension testing based on ASTM E2783 that the non-antimicrobial soaps did not have rapid biocidal activity. The Test Soap and Reference Soap A demonstrated <1 log10 reduction of ted skin , the difSkin compatibility plays an important role in product usage and, at times, may be the dominant factor. The FCAT study demonstrated no significant differences in skin barrier function between the Test Soap and Reference Soap B, a soap marketed for its mildness. In addition, there was no significant difference between the Test Soap and untreated skin, which is the strongest indication for mildness of the Test Soap. There was no significant difference in skin health when the Test Soap was applied to prewetted and nonwetted skin, demonstrating that the Test Soap can be applied to nonwetted hands. The advent of foam soaps, which do not need water to lather, challenges the need to prewet hands before handwashing as recommended in the CDC Hand Hygiene guideline .In this study, the Test Product was only compared with 1 reference product for each experiment. Additional studies should evaluate more formulations to identify the range of performance of commercially available non-antimicrobial soaps. This study outlines the multidimensional evaluation of hand hygiene products that must be performed to adequately inform product selections due to the complicated relationship between microbial removal, skin compatibility, and HCP acceptance and usage. Future multifactor studies should evaluate hand hygiene products under “real-world” test conditions including application times and doses that reflect actual clinical practice.Clinical effectiveness of hand hygiene products is dependent on their microbial reduction and HCP usage practices. As non-antimicrobial soaps become more prevalent in healthcare settings, controlled, standardized, and realistic evaluations of microbial removal and product acceptability—including skin compatibility and user experience—are needed to predict their effectiveness.


Choosing not to act, or the ability to intentionally inhibit your actions lies at the core of self-control. Even though most research has focused on externally primed inhibition, an important question concerns how intentional inhibition develops. Therefore, in the present study children (aged 10–12) and adults (aged 18–26) performed the marble task, in which they had to choose between acting on and inhibiting a prepotent response, while fMRI data were collected. Intentional inhibition was associated with activation of the fronto-basal ganglia network. Activation in the subthalamic nucleus and dorsal fronto-median cortex, regions which have previously been associated with intentional inhibition, did not differ between intentional inhibition and intentional action. Even though both children and adults intentionally inhibited their actions to a similar extent, children showed more activation in the fronto-basal ganglia network during intentional inhibition, but not in the subthalamic nucleus and dorsal fronto-median cortex. Furthermore, a positive relation between self-reported impulsivity and intentional inhibition was observed. These findings have important implications for our understanding of disorders of impulsivity, such as ADHD, which are associated with poor self-control abilities. A classical experiment to test self-control is the marshmallow experiment, a delay of gratification test for preschool children in which children can choose between one marshmallow now or two marshmallows later . StudiesAn important distinction which has been made in tasks that involve self-control, is whether the inhibitory process is externally or internally driven. Externally driven response inhibition involves the ability to interrupt an action when signaled by a cue in the environment, for example, a traffic light which turns red. Neuroscientific studies have shown that the fronto-basal ganglia network, with main nodes in right inferior frontal gyrus (rIFG), striatum, globus pallidus, and subthalamic nucleus (STN), is consistently involved during externally driven response inhibition e.g. . DevelopA second, but understudied component of self-control is intentional inhibition. In daily life often both external cues and internal processes play a role in the decision to inhibit, although sometimes external cues are more important (such as when stopping at a traffic light) and other times internal processes are more prominent (such as when inhibiting yourself from taking another piece of chocolate). However, in contrast to externally driven inhibition, intentional inhibition is not triggered by an external cue. Instead, intentional inhibition has been defined as a late internally driven veto process, a final opportunity to inhibit before action execution . Since iIn the present study, we used the child-friendly marble paradigm to examine the neural correlates of intentional action and inhibition in children. In this paradigm participants are instructed to freely decide between responding and inhibiting responding to a rolling marble. Children between 10 and 12 years of age were included to allow for comparison of the results to the externally driven response inhibition literature . Based oRecently, several studies have suggested that intentional inhibition is associated with increased activation in the dorsal fronto-median cortex (dFMC) , a regioIn order to validate our experimental measure of intentional inhibition, participants also completed the Barratt Impulsiveness Scale  outside 22.1M = 11.56, SD = .83) and twenty-four healthy right-handed adults between 18 and 26 years of age  participated in the experiment. The results from the adults have previously been published in a larger report on response inhibition (p = .92). All participants had normal or corrected-to-normal vision, and no neurological or psychiatric impairments according to self- or parent-report. Informed consent was obtained for all participants and the study was approved by the Internal Review Board at Leiden University Medical Center. In accordance with the guidelines of the Leiden University Medical Center, all anatomical scans were reviewed by a radiologist. No anomalous findings were reported.Nineteen healthy right-handed children between 10 and 12 years of age  and age groups did not differ in estimated IQ scores, F  = .00, p = .99, η2 = 1.04−6.To obtain an estimate of cognitive functioning, children and adults completed the subtests similarities and block design of the Wechsler Intelligence Scale for Children (WISC)  and the 2.2The marble task was adapted from In the green marble condition, the white marble changed to green as soon as it started rolling. The task was programmed in such a way that participants viewed 16 rapidly presented static pictures showing the marble at successive locations on the ramp, which was experienced as a rolling movement. Participants were instructed to stop the marble from crashing by pressing a response button with their right index finger. When participants were successful at stopping the marble, they were presented with a feedback screen showing the location where they had stopped the marble. When participants were not successful at stopping the marble, they were presented with a feedback screen showing a shattered marble beneath the ramp. The speed of the marble was adjusted by a staircase-tracking procedure. At the start of the experiment, the static pictures were presented for 30 milliseconds each. When participants were successful at stopping the marble the duration was decreased with 10 milliseconds, making the task more difficult. When participants were not successful at stopping the marble in time the duration was increased with 10 milliseconds, making the task easier. The staircase procedure was allowed to fluctuate between 20 and 80 milliseconds, allowing a response window between 320 and 1280 milliseconds.In the white marble condition, the marble did not change color and participants were instructed to choose between responding and inhibiting. When participants responded, they were presented with a feedback screen showing the location where they had stopped the marble. When participants inhibited, they were shown a feedback screen showing the white marble at the bottom of the ramp. In order to motivate participants to balance the frequency of responding and inhibiting, they were told that the stopped and non-stopped marbles would fall in different baskets. Participants were instructed to collect an equal amount of marbles in each basket, but were not allowed to count or use a sequencing strategy; therefore, participants were instructed to make an independent decision every time the marble stayed white. At the end of each block participants were shown how many marbles they had collected in each basket. As will be described in the results section, the participants were successful in following the instruction to stop the marble on approximately 50% of the trials.In order to give participants sufficient time to decide between responding and inhibiting the speed of the white marble rolling down the ramp was set considerably slower. The speed of the sequentially presented static white marble pictures was set to the speed currently reached in the green marble condition plus 30 milliseconds. Consequently the duration of the sequentially presented static white marble pictures was allowed to fluctuate between 50 and 110 milliseconds, allowing a response window between 800 and 1760 milliseconds.The experiment consisted of three blocks of 80 trials, each block consisting of 48 green and 32 white marble trials. Trials were presented in a pseudo-randomized order so that each white marble trial was preceded by 0, 1, 2, or 3 green marble trials. The large proportion of green trials served two functions. First, the green trials lead to a prepotent tendency for action. Since the green marble trials were rather difficult, participants had to remain focused on the goal of responding quickly to the rolling marble, thus increasing the prepotency of responding. Also, due to the intermixed presentation of green and white trials participants could not predict when a white trial would be presented. Therefore participants had to be prepared to quickly respond to a green marble during the whole duration of the experiment, leaving the prepotency intact. This was desirable, so that intentional inhibition of action would involve a late brake on an already-prepared action, rather than a decision not to initiate action preparation. Second, the randomized interleaving of intentional (white) and instructed (green) trials also discouraged participants from strategically pre-deciding a pattern of intentional action, such as act-inhibit-act-inhibit, etc.2.3Following the scanning session participants completed the Barratt Impulsiveness Scale (BIS-11) . The BIS2.43 voxels, field of view = 224 × 168 × 177 mm3). Head motion was restricted by using foam inserts between the head and the head coil. Visual stimuli were projected onto a screen in the magnet bore that could be viewed through a mirror attached to the head coil.Scanning was performed with a standard whole-head coil on a 3.0 Tesla Philips scanner at the Leiden University Medical Center. The marble task consisted of 3 event-related runs, each lasting approximately 6 min. Functional data were acquired using T2*-weighted echo-planar imaging (EPI). The first 2 volumes of each run were discarded in order to allow for equilibration of T1 saturation effects . After the functional runs a high-resolution 3D T1-FFE scan for anatomical reference was obtained  index using 2.6F  = .043, p = .84, η2 = .001. Structural and functional volumes were spatially normalized to T1 templates. The normalization algorithm used a 12-parameter affine nonlinear transformation involving cosine basis functions, and then resampled the volumes to 3-mm cubic voxels. Templates were based on the MNI305 stereotaxic space . Images were corrected for rigid-body motion. Translational movement did not exceed 1 voxel (<3 mm) and mean movement did not differ between age groups, ic space , an appric space . Functiohttp://marsbar.sourceforge.net). ROIs that spanned several anatomical regions were masked with marsbar-aal ROIs. For rSTN, ROI analyses were performed on an anatomical rSTN template derived from a study using ultrahigh 7 Tesla scanning (Region of interest (ROI) analyses were performed to further characterize the involvement of brain regions in the development of intentional inhibition. ROI analyses were performed with the MarsBaR toolbox in SPM8  (http://scanning . For dFMscanning .33.1SD = 7.06). However, despite the tracking, adults  were more successful at responding to the green marble in time compared to children , F  = 8.68, p < .01, η2 = .17 . However, as can be seen in F  = 4.92, p< .05, η2 = .11.The first comparison looked at performance on the instructed green marble trials. The staircase-tracking procedure for green marble trials was overall successful, showing that participants responded in time on 60.63% of the trials  was observed. To examine the randomness of the participants’ choice behavior, the participants’ RNG2 index was compared with a RNG2 index computed over a set of randomly generated sequences of go- and nogo-responses. For the randomly generated set of go- and nogo-response sequences a mean RNG2 index of .801 (SD = .002) was observed. Although the RNG2 index for the randomly generated sequences was marginally but significantly smaller compared to the participants’ RNG2 index, F  = 18.90, p < .001, η2 = .22, these results indicate that the participants’ behavior was close to being random and not driven by simple alternation strategies. Children and adults did not differ in RNG2 index, F  = 1.20, p = .28, η2 = .03, indicating that children and adults did not differ in use of strategies for deciding between responding and inhibiting.To examine the use of response selection strategies the RNG2 index was computed. A mean RNG2 index of .81  = 60.79, p < .001, η2 = .60  = .84, p = .37, η2 = .02, or interaction, F  = 1.47, p = .23, η2 = .04, effects of age group were observed.Next, we examined whether there were differences in response times to the instructed green and intentional white marble trials. As expected, reaction times on the green trials were shorter compared to the white trials,  .60 see , indicatp's > .1) .No developmental differences in self-reported impulsivity on the BIS-11 were observed  see . However .73 see . However .17 see . A compa3.2N = 43). This analysis revealed activation in a fronto-basal ganglia network, including bilateral IFG, bilateral striatum, and occipital lobe, but not in the STN and the dFMC . To further examine the involvement of the fronto-basal ganglia network in intentional inhibition across development, ROI analyses were performed for the rIFG, right putamen, right caudate, and right globus pallidus.To identify the brain regions involved in intentional inhibition, the contrast intentional inhibition > intentional action (White NoGo > White Go) was computed for the whole group  = .29, p = .59, η2 = .01. However, there was a trend for an age group × condition interaction, F  = 3.71, p = .061, η2 = .08, indicating that children showed significantly more rIFG activation for intentional inhibition compared to intentional action, F  = 25.21, p < .001, η2 = .0 = 58, whereas adults did not, F  = 2.05, p = .17, η2 = .08  = .91, p = .35, η2 = .02. However, an age group × condition interaction, F  = 6.92, p < .05, η2 = .14, indicated that the activation difference between intentional inhibition and intentional action in right putamen was larger for children, F  = 29.93, p < .001, η2 = .62, than for adults, F  = 4.03, p = .057, η2 = .15  = 18.09, p < .05, η2 = .10  = 2.25, p = .14, η2 = .05.For right caudate there was a main effect of age group, showing that children had more stimulus related deactivation compared to adults,  .10 see . HoweverF  = .38, p = .54, η2 = .01. However, an age group × condition interaction, F  = 7.28, p < .05, η2 = .15, indicated that children showed relatively more right globus pallidus activation during intentional inhibition compared to intentional action, F  = 23.12, p < .001, η2 = 56, than adults, F  = 2.86, p = .10, η2 = .11  = 2.96, p = .09, η2 = .07. No main, F  = .86, p = .36, η2 = .02, or interaction effects, F  = .18, p = .68, η2 = .004, of age group were observed . However, when looking at the intentional inhibition decision process (White NoGo > Green Go) and the intentional action decision process (White Go > Green Go) separately, clear bilateral STN activation was observed for both intentional inhibition and intentional action  = .43, p = .52, η2 = .01. Also, no main, F  = .12, p = .76, η2 = .003, or interaction effects, F  = .01, p = .94, η2 = .00, of age group were observed.No dFMC activation during intentional inhibition was observed in the contrast intentional inhibition > intentional action (White NoGo > White Go). To make sure that there indeed were no differences in dFMC activation, a ROI analysis was performed for dFMC. This analysis showed that dFMC activation did not differ between intentional inhibition (White NoGo) and intentional action (White Go), 3.2.3N = 43). No effects were observed at the FDR corrected threshold. However, for non-planning impulsivity a significant relationship with intentional inhibition related brain activation in the left putamen was observed at an uncorrected threshold , such that participants who reported more impulsivity showed more activation in left putamen during intentional inhibition . This is opposite to the relation observed between impulsivity and externally driven response inhibition; there more impulsivity is predictive of worse inhibitory performance . The posA continuing debate in research on intentional inhibition is the role of the dFMC. Some studies, including the study by Some limitations of the present study deserve mentioning. First, we only included a selected age-range (10–12 year-olds and 18–26 year-olds) in the present study. Future studies should include participants across the whole age range from early childhood to adulthood, to examine whether there are specific developmental periods during which intentional inhibition is most sensitive to developmental change (see also: To conclude, the present study was the first to examine the neural correlates of intentional inhibition in children and adults. Although children performed at adult level, children showed increased recruitment of the fronto-basal ganglia network during intentional inhibition. Individual differences in impulsivity were predictive of intentional inhibition, more impulsive people were more likely to choose to inhibit. This research has implications for research into disorders of impulsivity, such as ADHD, which are currently associated with poor self-control abilities . Many tyThere is no conflict of interest.


We find that blocking inhibition quenches variability of responses evoked by repeated stimuli and enhances discrimination between stimuli that invade the network from different spatial loci. Enhanced stimulus discrimination is reserved for representation schemes that are based on temporal relation between spikes emitted in groups of neurons. Our data indicate that – under intact inhibition – the response to a given stimulus is a noisy version of the response evoked in the absence of inhibition. Spatial analysis suggests that the dispersion effect of inhibition is due to disruption of an otherwise coherent, wave-like propagation of activity.Much of what is known about the contribution of inhibition to stimulus discrimination is due to extensively studied sensory systems, which are highly structured neural circuits. The effect of inhibition on stimulus representation in less structured networks is not as clear. Here we exercise a biosynthetic approach in order to study the impacts of inhibition on stimulus representation in non-specialized network anatomy. Combining pharmacological manipulation, multisite electrical stimulation and recording from  In neural systems, inhibition seems to enrich the repertoire of activity patterns in the developing as well as the mature brain10; there is evidence to that effect also at the behavioral level13. Much of what is known of the impacts of inhibition in these systems comes from analyses of the sensory envelope. There, where the connectivity of inhibitory neurons is relatively stereotypic and where stimulus evoked activity can be meticulously analyzed, inhibition is underlying a core trait shared by all modalities: sharpening of stimulus selectivity and contrast sensitivity by means of lateral inhibition, which depends on a unique structural configuration18. Downstream the sensory envelope, where activity travels through less specialized structures, the impacts of inhibition on sensory processing are less clear, and the involvement of lateral inhibition is debated22.Inhibition is a key determinant of structural and functional pattern formation in a wide range of biological phenomena24, the present study implements control of inhibition by application of Bicuculline (blocking GABAA receptors and Ca2+ dependent K+ channels). We studied the impacts of this pharmacological manipulation of inhibition on trial-to-trial variability and on discrimination between stimuli that invade the network from different spatial loci in the electrode array.Here we investigate the impacts of inhibition on stimulus evoked activity, disentangled from the effects enforced by specialized structures. To this aim we record and analyze responses to stimuli before and after partial blocking of inhibition in large-scale random networks of cultured cortical neurons, using an array of extracellular electrodes. While ‘not-a-brain’, the setup offers an opportunity to study the effects of inhibition under weaker structural constrains, at high temporal resolution, in multiple sites and with good pharmacological control over the extent of inhibitory activity. Acknowledging the existence of many different mechanisms that potentially contribute to network inhibitionThe reported results suggest that blocking inhibition in random networks reduces response variability and sharpens the sensitivity of activity to stimulus location. The extent to which inhibition impacts on stimulus discrimination depends on the type of response features taken into consideration. Interestingly, the response patterns exposed in the presence of Bicuculline share information with those detected in intact networks, suggesting that in a randomly rewired network inhibition acts as a disperser. The data indicate that the dispersion effect of inhibition is due to interference with wave-like propagation of activity through nearest neighbors, which is akin - in a certain sense - to the mechanism by which lateral inhibition sharpens stimulus contrast.Two related aspects of network response were studied: variability in responses to repeated stimuli delivered through the same spatial location , and separability of responses to stimuli delivered at different spatially located electrodes. In the latter (separability) set of experiments, we insisted on analyzing responses of the same group of neurons to the different stimulation sites, thus mimicking a case where different stimuli are processed by the same cell assembly.rate and temporal relations between spikes recorded in different electrodes. The rate features used are population firing rate summed over all electrodes , a concentration that significantly reduces neuronal inhibition, but not to an extent leading to seizure-like activity26 (see Methods). Trial-to-trial variability was evaluated under each condition: the intact and the inhibition-blocked network. As previously reported27, in the presence of Bicuculline the networks show enhanced responsiveness to stimulation. Each response terminates within ∼1 second (and often less), congruent with the timescales of in-vivo cortical responses under anesthetized conditions where inhibition is reduced28. Blocking inhibition reduces variability across trials when compared to the intact network; this effect is observed in all response features tested. Figure 29.Responses to repeated input from a single stimulation source were recorded before and after bath application of 4–5 The reduction in response variability across our data set may be quantified by cluster analysis (see Methods): for each response feature and under each condition, a hierarchical tree of responses is constructed based on pairwise distances ; indeed, within this frequency range variability is reduced for all stimulation rates and all features , and evaluated separability of responses to the different sources using unsupervised separation as well as supervised classification procedures. We were particularly interested in the more challenging task of stimulus discrimination that is based on the activity of non-selective neurons that respond to all stimulation sites. We therefor selected the group of electrodes in which responses were reliably detected for all stimuli, across conditions (see Methods), a context that may be mapped to a scenario of different stimuli being processed by the same cell assembly. As shown below, in the presence of Bicuculline discrimination based on the relation between spike times recorded in different electrodes becomes sharper; discrimination remained unchanged (on average) when based on rate features.Given the stereotypic response to a single stimulation source, induced by blocking inhibition, how does blocking inhibition affects the discrimination of stimuli delivered from different spatial sources? One may imagine two extreme cases: (1) block of inhibition increases network symmetry, collapsing the response down to a single pattern, irrespective of the stimulation site. Alternatively, (2) block of inhibition breaks network symmetry, generating a unique response to each input source; a stiff “lookup table”. We thus proceeded to examine the network response to randomly alternating stimulation sites  before and after bath application of Bicuculline  is calculated based on intra-source and inter-source distances (see Methods). Overall, the contrast between pairs of stimulation sources increases in the presence of Bicuculline when estimated from recruitment order Fig.  and FSL Support vector machine  was implemented in order to evaluate discrimination of individual responses to stimuli delivered from two or four different sites. Congruent with the results of the above unsupervised protocol, classification accuracy is improved in the presence of Bicuculline when estimated from recruitment order Fig.  and FSL The overall picture seems consistent with a scenario in which blocking the inhibition partitions the network to different, stiff propagation paths; hence discrimination that is based on spike time relations (but not rate) becomes sharper.33. We examined the above-reported observations as reflecting noise contributed by inhibition to an otherwise (relatively) noise-less neural activity. To that end, a noisy version of the data recorded in the presence of Bicuculline was generated, by randomly jittering the spike-time series to varying widths. Indeed, a jitter of ca. ∼10 ms recovers the characteristic trial to trial response variability of the intact network  is sharpened as a function of the distance between stimulation sites. Stimulus discrimination that is based on rate features is unaffected. Both of these observations are incongruent with the notion of inhibition as a means to enhance network ability to differentiate between stimuli. This discrepancy in the role taken by inhibition may be related to the target of our analyses: we were interested in how the 49, however their role is unknown and their existence is considered baffling in the light of stimulus selectivity of cortical cells. Our results suggest that traveling waves may engage a complementary representation strategy to that of stimulus selectivity — carrying information about the stimulus identity within the spatio-temporal activity patterns of non-selective cells.The overall reduced response variability and improved stimulus discrimination under blocked inhibition are accompanied by coherent traveling waves originating from the stimulation site. Traveling waves of comparable propagation velocity .The data is consistent with the interpretation that inhibition in large random networks mimics lateral inhibition, at least in the sense of interrupting the propagation of excitation to nearby neighbors. The spontaneous emergence of such effective lateral-inhibition impact in randomly rewired networks could arise from the fast and coherent manner by which inhibitory activity propagates through strong electrical coupling54, inhibitory neurons decorrelate network models56, and blocking inhibition reduces variability39.We further show that responses under control conditions are “noisy” (or variable) versions of the reproducible responses in the absence of inhibition. This conclusion is consistent with indications in the literature, pointing to inhibition as contributing to variability. Thus, for instance, inhibitory synapses change more rapidly59.Overall, the observations reported in this research imply that in random networks inhibition enhances the repertoire of activity patterns, shortens activation path between distal cells, and impacts on the resolution of telling stimuli apart. It is tempting to contemplate the E/I ratio as a dynamic variable that may enhance or restrict network plasticity and enables adaptation of network states to tasks carried by the same cell-assembly60. Rats were anesthetized by CO2 inhalation according to protocols approved by the Technion’s ethics committee. All procedures involving cell preparation and animals handling were performed in accordance with these guidelines and regulations. The neurons were isolated and plated directly onto substrate-integrated multi electrode arrays. They were allowed to develop into functionally and structurally mature networks over a period of 2 weeks and were used in experiments within the period of 2–6 weeks post plating. The plated neurons cover an area of about 380 mm2, bathed in Minimum Essential Medium Eagle (Sigma), supplemented with heat-inactivated horse serum (5%), glutamine (0.5 mM), glucose (20 mM), and gentamycin (10 μg/ml), and maintained in an atmosphere of 37 °C, 5% CO2 and 95% air in an incubator as well as during the recording phases. An array of 60 Ti/Au extracellular electrodes, 30 μm in diameter, spaced 500 μm from each other  was used. The insulation layer (silicon nitride) is pretreated with polyethyleneimine .Cortical neurons were obtained from newborn rats (Sprague-Dawley) within 24 hours after birth using mechanical and enzymatic procedures described in earlier studies61, we used threshold-based algorithm for spike detection, therefor our recording conditions are strongly biased to picking up signals from cell bodies. We have used a Simulink-based software for on-line control of data collection [see Zrenner et al. (2010) for details]. Voltage stimulation was applied in the form of a mono-phasic square pulse 200 μsec. 800–950 mV through extracellular electrodes using a dedicated stimulus generator . Action potentials timestamps were detected on-line by threshold crossing of negative voltage. Detection of synchronous events  was performed off-line using a previously described algorithm62 based on threshold crossing of the network firing rate (binned to 3 msec). Once a NS was detected within 400 millisecond following a stimulus, action potentials recorded in all the electrodes within 500 ms following the stimulus were extracted. Post-stimulus time histograms were constructed using a 1 ms time bin, and smoothed with a 5 ms moving average; responses were then screened for a maximum amplitude of at least 1.5 spikes/ms. As indicated above, the recording conditions were kept identical to the incubation conditions; i.e: bathed in Minimum Essential Medium Eagle (Sigma) that was supplemented with heat-inactivated horse serum (5%), glutamine (0.5 mM), glucose (20 mM), and gentamycin (10 μg/ml), and maintained in an atmosphere of 37 °C, 5% CO2 and 95% air. We performed two types of experiments: in the first, repeating stimuli were applied through a single electrode at a constant interval (5–8 seconds), under control conditions (intact inhibition) and in the presence of Bicuculline, a blocker of fast GABA transmission . In the second type of experiments we provided stimuli from several electrodes  in random orders but at constant intervals (4–8 seconds), under control conditions and blocked inhibition (2–8 μM Bicuculline). In 2 out of 9 networks used for stimulus classification experiments, the basal responsiveness was low; in these two cases we have used 1 μM Bicuculline to increase baseline responsiveness. For blocked inhibition conditions, Bicuculline bath application was administrated as following: we first added 1 or 2 μM of Bicuculline, and waited 10 minutes to make sure that the substance impact has stabilized, and then shortly tested the responsiveness from all sources. We then decided whether to add more Bicuculline based on 3 indicators for the level of the blockade: response probability, response latency and response duration27. In case response latency was still longer then ca. 50 ms, and response probability has not increased for all sources, we increased the dose in 2 μM steps. In all our experiment, responses did not sustain beyond ca. one second.A commercial amplifier  with frequency limits of 150–3,000 Hz and a gain of x1024 was used for obtaining data. Data was digitized using an acquisition board . Each channel, sampled at a frequency of 16 kHz, detects electrical activity that might be originated from several sources  as the recording electrodes were surrounded by several cell bodies. Action potentials originating from cell bodies are typically an order of magnitude stronger than axonal action potentialsFirst spike latencies were calculated from a subset of the 8 most active electrodes. In cases of a failure to participate in a response, a random value was assigned, pooled from a uniform distribution over the interval [10–500] ms. This choice was taken in order to avoid trivialization of response classification by support vector machine (SVM) according to the missing electrodes. Similar results of the agglomerative analysis (see below) are obtained when these random values were replaced with zeros.Action potentials recorded within 500 ms following each stimulus were used for the extraction of different response features. Generally, a minimum participation in 90% of stimuli was set as a limit for inclusion of a channel (electrode) in the analysis of all response features; in analyses of population rate, all electrodes were used. Recruitment order was defined as the rank of the electrodes, ordered according to their first spike latencies; cases of missed response were assigned an averaged rank .Distances were computed for pairs of response feature vectors with a 1 − cos(α) metric. Similar results to those reported here were obtained using other metrics . Distances were computed for 40 responses from each of the single source experiments (n = 8 networks), and 40 responses from each source for experiments with multiple stimulation sources (n = 9 networks).Supervised and unsupervised classification procedures were used to quantify dispersion of responses from single sources, as well as for evaluating separability of responses from multiple stimulation sources. To evaluate response dispersion for repeated inputs from a single source, a hierarchic tree was constructed for each network  metric); on each iteration the most proximal distance value was taken as the distance between pairs of clusters. Cutoffs limiting the maximal distance allowed between two clusters were implemented. To evaluate separability of responses from multiple sources, a Contrast measure adopted from Beggs and Plenz (2004) was calculated for pairs of sources , defined as follows:Din is the sum of distances between all pairs of responses to a given stimulation source, Dout being the sum of distances between all pairs of inter-source responses (responding to two different stimulation sources), using the distance metric of 1 − cos(α). Note that this measure relies on the ground truth of stimulation identity, and thus only evaluates the relative goodness of separation across conditions.Support Vector Machine (SVM) with a Gaussian radial basis function (RBF) kernel, as well as a linear kernel, were used to classify responses from 2 or 4 sources (n = 40 responses per source). Classification performances were averaged over 50 repetitions for each classification process . For SVM of population rate histograms with a Gaussian radial-based kernel, only the 10–70 ms range were used.Conditional Firing Probabilities (CFP)37 were computed for all pairs of electrodes, with a minimal activity threshold of 100 spikes per electrode (within 500 ms from stimulus onset). Binary representations of single electrode firing rate were generated with a temporal resolution of 2 ms. The conditioned probability for electrode i to fire at time t = t′ + τ, given that electrode j fired at t = t′, was computed for τ =  at 2 ms steps. The resulting profiles of the CFP were then smoothed with a moving average of 3 consecutive values. The first maximum of each profile was extracted along with its index, which is referred to as the “typical delay”. CFP profiles with a maximum lower than 0.05 were excluded. The typical delays were then averaged for distances between electrode i and j over data pooled from 8 networks.Statistical inference was used to support the trends we recognize as being induced by blocking inhibition. In all cases, at least one of the datasets (i.e control or blocked inhibition) stray from a normal distribution at the tails. We therefore opted to use only non parametric tests. We used paired Wilcoxon signed rank test for either right or left tail, as indicated in the text where the distribution evaluated is [control feature]−[blocked inhibition feature]. Wherever correlation between 2 variables is estimated, we used Spearman correlation. P-values and correlation values are stated within figure captions.LaTeX Supplementary FileSupplementary material


Glaciers cover ~ 10% of land but are among the least explored environments on Earth. The basal portion of glaciers often harbors unique aquatic microbial ecosystems in the absence of sunlight, and knowledge on the microbial community structures and their metabolic potential is very limited. Here, we provide insights into the microbial lifestyle present at the base of the Matanuska Glacier, Alaska.DNA and RNA were extracted from samples of the Matanuska Glacier basal ice. Using Illumina MiSeq and HiSeq sequencing, we investigated the microbial diversity with the metagenomic shotgun reads and 16S ribosomal RNA data. We further assembled 9 partial and draft bacterial genomes from the metagenomic assembly, and identified key metabolic pathways such as sulfur oxidation and nitrification. Collectively, our analyses suggest a prevalence of lithotrophic and heterotrophic metabolisms in the subglacial microbiome.Our results present the first metagenomic assembly and bacterial draft genomes for a subglacial environment. These results extend our understanding of the chemical and biological processes in subglacial environments critically influenced by global climate change.The online version of this article (10.1186/s40168-018-0505-5) contains supplementary material, which is available to authorized users. Subglacial ecosystems are associated with hydrological networks at the base of glaciers and ice sheets that transport water discharged proglacially or into the ocean . The rolBasal ice forms in the deepest portion of a glacier where the ice is in direct contact with the underlying bedrock, and its composition and structure become altered through interactions with glacier bed . Basal pThe Matanuska Glacier is a large, terrestrial valley glacier located in the Chugach Mountains of Southcentral Alaska, approximately 138 km north of Anchorage. It flows north ~ 45 km from the Ted Stevens Ice Field and ranges in width from ~ 3 km near the equilibrium line to ~ 5 km along its terminus , 14–16 pde novo and to assess the metabolic activity of specific microbial taxa based on 16S rRNA to rDNA ratios.In this study, we examined the microbial community inhabiting the basal ice layer from Matanuska Glacier, Alaska, using 16S rRNA gene (rDNA), 16S rRNA transcript (rRNA), and metagenomic sequencing analysis. These data were used to assemble 9 partial and draft bacterial genomes Samples of exposed basal ice at the terminus of the Matanuska Glacier  , Synthrophus (Bin 2732 and Bin 31), and Thiobacillus (Bin 04), whereas the other 4  were unclassifiable and only identified as bacteria. The genomic statistics  for the 9 GBs are summarized in Additional file Assembly of the metagenomic sequencing data allowed the recovery of 9 partial and draft genomes (further referred as Genome Bins (GBs)) with a completion level ≥ 70% and contamination level ≤ 10%  and relatively lower NO3 concentration (60 ppb). These measurements suggested that sulfate and nitrate reduction could also be prevalent in the basal ice of Matanuska Glacier. Functional analysis of the GBs identified components of lithotrophic pathways, but likely due to incompleteness, intact pathways within a single draft genome were not recovered. Dissimilatory adenylylsulfate reductases (aprA and aprB) and sulfur oxidizing (soxB) genes were present in Bin 04  for energy production. Furthermore, Bin 04 also possessed genes of dissimilatory nitrate reductases (narGHI and napA) and nitrite oxidoreductase (nxrA), implying the capability to utilize nitrate as terminal electron acceptor in anaerobic respiration. The presence or absence of key pathways and genes in the Matanuska basal ice layer GBs are summarized in Additional file In the absence of light, chemolithotrophy may support biogeochemical processes in the subglacial environment , 20–22. 04 Table . The ide2 fixation enzymes, especially Ribulose bisphosphate carboxylase (RuBisCO), were also identified in Bin 04. The ability to perform CO2 fixation supports the hypothesis for microbial lithoautotrophic metabolism via sulfur oxidation. The GBs also contained genes related to cold and oxidative stress tolerance: Bin 11 and Bin 31 contained genes of cold shock protein (cspA), whereas Bin 04, Bin 0236, and Bin 2732 possessed genes of catalase and superoxide dismutase.Genes of carbon metabolism pathways in the GBs were mostly involved in central carbohydrate metabolisms such as glycolysis, gluconeogenesis, and pyruvate metabolism  from a single glacier. More thorough sampling and analysis of multiple basal ice cryofacies  and different glacier types  are necessary to establish a comprehensive understanding of the diversity and function of microbial communities inhabiting the basal zones of glaciers. Despite the limitations, our results may be used in several downstream studies such as comparative analysis of the basal ice zones and other glacial environments. The draft genomes obtained by this study may also be important for comparative genomics and evolutionary studies.Additional file 1:Supplementary Information. (PDF 1581 kb)Additional file 2:Supplementary Tables. (XLSX 142 kb)


Cell-based therapy using dendritic cells (DC) represents a potent cancer immunotherapy. However, activated DC express indoleamine 2,3-dioxygenase 1 (IDO1), a counter-regulatory and tolerogenic molecule, leading to the inhibition of T cell activation and the promotion of T cell differentiation into regulatory T cells. Silencing the IDO1 gene in DC by small interfering RNA (siRNA) represents a potent therapeutic strategy. We report on the successful and efficient introduction of a siRNA targeting IDO1 into mouse DCs by a means of a multifunctional envelope-type nanodevice (MEND) containing a YSK12-C4 (YSK12-MEND). The YSK12-C4 has both fusogenic and cationic properties. The YSK12-MEND induced an effective level of gene silencing of IDO1 at siRNA doses in the range of 1–20 nM, a concentration that commercially available transfection reagents are not able to silence. The YSK12-MEND mediated IDO1 silencing had no effect on the characteristic determinants of DC phenotype such as CD11c, CD80 and MHC class II. The silencing of IDO1 in DC by the YSK12-MEND significantly enhanced the antitumor effect against E.G7-OVA tumor. Moreover, a decrease in the numbers of regulatory T cells in the tumor was observed in mice that were treated with the IDO1-silenced DC. The YSK12-MEND appears to be a potent delivery system for IDO1-silenced DC based cancer immunotherapy. Thus, DC-based therapy represents a potent approach in cancer immunotherapy and this approach has been extensively developed. The first FDA-approved cell-based therapy, Provenge (Sipuleucel-T), was composed of activated blood mononuclear cells including DCs, and was used for the treatment of prostate cancer. However, this approach was a subject of criticism, because the effect was not as strong as would be expected3. The cause of the modest efficacy can be attributed to the immune suppressive characteristics of the tumor-associated microenvironment. It is now well-known that effector immune cells such as DCs, cytotoxic T cells (CTLs), helper T cells are functionally suppressed by several mechanisms such as a loss of immunogenicity, immune check point molecules, immune suppressive molecules, regulatory T (Treg) cells and myeloid-derived suppressor cells (MDSCs)5. Given this situation, DC-based therapy combined with the inhibition of immune suppression are currently being investigated in preclinical and clinical investigations6. On the other hand, stimulation by adjuvants or cytokines leads to the upregulation of counter-regulators, such as the suppressor of cytokine signaling 1 (SOCS1), A20 and indoleamine 2,3-dioxygenase-1 (IDO1), in immune responses in DCs10. Therefore, the inhibition of these counter-regulators represents a promising strategy for enhancing the efficacy of DC-based therapy15.Dendritic cells (DCs) are one of the most powerful antigen presenting cells (APCs). The engulfment of antigens and the cross-presentation of antigens by DCs represents a critical bridge between innate and adaptive immunity. In cancer, the sensing of cancer cells or tumor antigens by DCs stimulates a sequence of anti-tumor immune responses16. IDO1 activity is upregulated in many types of human cancer and tends to be associated with a poor prognosis17. The depletion of tryptophan by IDO1 leads to the suppression of effector T cells, the differentiation of naïve T cells to Treg cells, the functional promotion of MDSCs and the recruitment of tumor vasculature18. IDO1-expressing DCs induce several types of negative regulation including the inhibition of T cell priming and proliferation, and the differentiation of naïve T cells to Treg cells19. Therefore, the inhibition of IDO1 in DCs is considered to be a promising strategy for enhancing the efficacy of DC-based therapy, because the activation of DCs by adjuvants or cytokines in vitro promotes the expression of IDO1.Increasing evidence indicates that IDO1, an enzyme associated with tryptophan metabolism, greatly contributes to the immune suppression in a tumor-associated microenvironmentin vitro. DCs in which IDO1 is silenced by siRNA show enhanced immuno-stimulative activities and the efficacy of DC-based therapy is enhanced against cancer20. In these reports, however, high levels of siRNA (2 μg) or electroporation methodology were used to introduce the siRNA into DCs. The requirement of a high dose and special equipment detracts from the potentially broad utility and practical application of this approach. Thus, a delivery system that can efficiently introduce siRNA into DCs, is easily handled, and does not require special equipment, would be highly desirable in this regard. Although transfection reagents for delivering siRNA into cells are in widespread use, some of which are commercially available (Lipofectamine® RNAiMAX (RNAiMAX), X-tremeGENE, ViaFectTM, etc), delivering siRNA to immune cells, for example DCs, T cells, B cells, natural killer (NK) cells and macrophages, by these commercially available reagents is quite difficult.Gene silencing by small interfering RNA (siRNA) is powerful and straightforward approach for inhibiting the expression of target genes 23 and we developed a MEND containing the YSK12-C4 lipid (YSK12-MEND) that can be used to deliver siRNA to several types of immune cells25. YSK12-C4 is a cationic lipid containing unsaturated carbon chains, which enhances endosomal escape. The YSK12-MEND resulted in a 90% gene silencing activity with a median effective concentration (EC50) of 1.5 nM in DC. On the other hand, the EC50 for RNAiMAX was 25 nM15. In addition, the DCs in which SOCS1 had been silenced by the YSK12-MEND showed drastically enhanced immuno-stimulative activities and the efficacy of cell therapy using the SOCS1-silenced DC in tumor bearing mice was increased substantially. These findings indicate that the YSK12-MEND represents a promising delivery system that can result in effective gene silencing using a low dose of siRNA and is easily handled.In the previous studies, we designed a multifunctional envelope-type nanodevice (MEND) for use as a non-viral delivery system for nucleic acidsWe report here on confirming the potency of the YSK12-MEND in IDO1-silenced DC-based therapy against cancer. For this purpose, we prepared an IDO1-targeting siRNA (siIDO1) that was loaded in the YSK12-MEND (YSK12-MEND (siIDO1)) and gene silencing efficiency was evaluated in mouse bone-marrow derived DCs (BMDCs). The silencing efficiency was 70% at a siRNA dose of 20 nM. The efficiency was overwhelmingly superior to commercially available transfection reagents. The DCs with IDO1 silenced by the YSK12-MEND showed a significantly enhanced antitumor effect against E.G7-OVA tumors. Moreover, the level of Treg cells in tumors was decreased in mice that had been treated with the IDO1-silenced DC. The findings reported herein demonstrate that the YSK12-MEND represents an effective delivery system for IDO1-silenced DC based cancer immunotherapy.25. We first developed YSK12-MENDs (siIDO1 or siCtl) and assessed their physical properties. The diameter, polydispersity index (PDI), zeta-potential and siRNA encapsulation efficiency between the YSK12-MEND (siIDO1) and the YSK12-MEND (siCtl) were comparable , and Silencer siRNA , respectively. The siIDO1 used in the present study was an ON-TARGET plus siRNA . Although the sequence, chemical modification and composition were different, the YSK12-MEND could be similarly used to encapsulate siRNA. This confirms that the YSK12-MEND can be used to encapsulate various types of siRNA.We previously reported on the preparation of siRNA , SOCS1 or GAPDH)-loaded YSK12-MENDs14. BMDCs were treated with IFN-γ for 2 h, followed by a 24 h culture period, and the expression of IDO1 at the mRNA level was measured. The expression of IDO1 in BMDCs treated with IFN-γ was 2.7 times higher than that of control BMDCs  was used26. In this study, we used 134 ng (20 nM) of siRNA  for the transfection of 6 × 105 of BMDCs. We also evaluated the silencing efficiency of commercially available transfection reagents at the same siRNA doses as were used for the YSK12-MEND. As a result, RNAiMAX  in BMDCs. The expression of IDO1 in BMDCs was very low in the steady state. Thus, the upregulation of the IDO1 gene is needed in order to evaluate the gene silencing effect. An interferon-γ (IFN-γ) treatment upregulated the expression of IDO1 in DCsDCs Fig. . After sDCs Fig. . The silMAX Fig.  and GeneMAX Fig.  failed t24. Thus, the low cellular uptake in the case of RNAiMAX can be attributed to its large size. On the other hand, in spite of the large size of the GeneSilencer, it showed a higher cellular uptake than the YSK12-MEND and the RNAiMAX. It is likely that the GeneSilencer had a unique affinity for BMDCs and the high fluorescence intensity that was observed can be attributed to the incorporation of large size particles.We subsequently compared the efficiency of cellular internalization between the YSK12-MEND and the commercially available transfection reagents. BMDCs were treated with a Cy5-labeled siRNA (Cy5-siRNA) loaded YSK12-MEND, RNAiMAX and GeneSilencer at siRNA doses of 10 and 20 nM, followed by the flow cytometry analysis. In the histograms, a substantial shift was observed in the BMDCs that had been treated with GeneSilencer Fig. . The rel15. Furthermore, it is important top note that the shape of the histogram of the BMDCs incorporating the YSK12-MEND was very similar to the histogram for untreated BMDCs  were analyzed by flow cytometry. The CD11c is a major DC marker and the number of CD11c+ cells are generally evaluated. The CD40, CD80, CD86 and MHC-II are used as a maturation marker and the change of expression level is generally evaluated. As a control, we used IFN-γ non-treated BMDCs (immature BMDCs). We normalized the obtained FI values (geometric mean: GeoMean) by that for non-treated BMDCs (without IFN-γ and antibodies). As a result, the percentages of CD11c+ cells were comparable among the samples, suggesting that the transfection and IDO1 silencing by the YSK12-MEND did not influence the character of BMDCs , the BMDCs were transfected with the YSK12-MEND (siIDO1 or siCtl). After 24 h, the percentage of CD11c15. The BMDCs were then pulsed with ovalbumin (OVA) and the SIINFEKL peptide, and were injected into mice bearing E.G7-OVA tumors on day 4, 8, 11 and 16. When gene-silenced DC, sustaining gene silencing is important. In the previous report, the YSK12-MEND maintained a gene silencing effect at protein level for 48 h after the treatment of immune cells24. In addition, we used ON-TARGET plus siRNA (Dharmacon) in this study. The siRNAs can have a high capability for sustaining gene silencing, because the siRNAs are chemically modified. The gene silencing of IDO1 was probably considered to last for more than 48 h. On the other hand, the migration of the injected DC to draining lymph nodes was observed at 12 h after the footpads were injected27. This fact indicates that gene silencing that can be sustained for at least 12 h or more would be sufficient. In the case of the BMDCs transfected with the YSK12-MEND (siIDO1), the tumor growth was significantly inhibited in comparison with that of the YSK12-MEND (siCtl) at 12 days after the E.G7-OVA inoculation . The previous result indicates that about 30% of the YSK12-MEND in the transfection medium was taken up by BMDCsion Fig. . In the ion Fig. , and theion Fig. . The eff19. In human patients, vaccination with IDO1-positive DCs was reported to result in an enhanced production of Treg cells34. To address this issue, we investigated changes in the Treg cell population in E.G7-OVA tumors after treatment with IDO1-silenced BMDCs. Tumor tissues were collected on day 18 of the antitumor experiment , compared with that of the YSK12-MEND (siCtl)  transcription factor that is expressed by naive T cells, leading to differentiation to Treg cells37. It is likely that the silencing of IDO1 by the YSK12-MEND reduces the involvement of IDO1-expressing DC treatment in these pathways in the differentiation to Treg cells.As pointed out above, one of the negative aspects of IDO1-expressing DCs is the differentiation of naïve T cells to Treg cellsent Fig. , and thetl) Fig. . In additl) Fig. . These r20. The enhancement in antitumor effect can be attributed to the reduction in the levels of Treg cells that are produced in the tumor microenvironment. The results indicate that the YSK12-MEND represents a promising system for achieving IDO1-silencing DC-based therapy against cancer. Similar to previous reports, the findings indicate that the use of siRNA for inhibition IDO1 activity in DCs represents an attractive strategy for reducing the levels of Treg cells in the tumor microenvironment. IDO1 is attractive target for inhibiting immune suppression, secondary to immune checkpoint molecules such as programmed death 1 (PD-1). More than 10 clinical trials using IDO1 inhibitors  have been initiated, and a year ago, the future of IDO1 inhibitors looked bright. However, the negative results associated with phase III trials using IDO1 inhibitors  that were reported in 2018 have dampened this enthusiasm and several companies have now cancelled, suspended, or downsized phase III trials using small-molecule drugs38. The capability of the drug, and not the target (IDO1), might be the problem. The target patients also might not have been suitable. Anyway, it is suggested that new strategy is required instead of small-molecule drugs. IDO1 knockdown by a YSK12-MEND represents an effective strategy for the IDO1 targeted therapy in the future.The findings reported here show that a YSK12-MEND efficiently silenced the IDO1 gene in BMDCs using a low dose of siRNA, and that the IDO1-silenced BMDCs promoted the antitumor effect mediated by DC-based therapy. The YSK12-MEND could be used to homogenously introduce siRNA to BMDCs compared with commercially available transfection reagents, and to induce a sufficient level of gene silencing at siRNA doses which the commercially available transfection reagents were nearly completely ineffective. This procedure is greatly superior to these used in previous studies15. Cholesterol was obtained from Avanti Polar Lipids Inc. . 1,2-Dimirystoyl-sn-glycerol methoxyethyleneglycol 2000 ether (PEG2000-DMG) was purchased from the NOF Corporation . RNAiMAX was obtained from Thermo Fisher Scientific . GeneSilencer was purchased from Genlantis . ON-TARGET plus Mouse Ido1 (15930) siRNA-SMART pool (IDO1-tageted siRNA: siIDO1) and ON-TARGET plus Non-targeting siRNA pool (control siRNA: siCtl) were obtained from Dharmacon . Cy5-siRNA (sense: 5′ -AcAuGAAGcAGcACGACuU(dT*dT)-3′; antisense: 5′-AAGUCGUGCUGCUUC AUGU(dTdT) Cy5-3′, 2′ -OMe are denoted in lower case letters and phoshorothioate linkages are represented by asterisks) was synthesized by BIONEER . Murine recombinant granulocyte-macrophage colony-stimulating factor (GM-CSF) was purchased from R&D Systems . Murine recombinant IFN-γ was obtained from PeproTech . Purified anti-mouse CD16/32 (Clone: 93), APC anti-mouse I-A/I-E (clone: M5/114.15.2), APC anti-mouse CD40 (clone: 3/23), APC anti-mouse CD80 (clone: 16-10A1), APC anti-mouse CD86 (clone: GL-1), PE anti-mouse CD11c (clone: N418), their isotype controls, and the 7-AAD Viability Staining Solution were obtained from BioLegend . OVA (grade VI) were obtained from SIGMA-Aldrich Co. . Peptide SIINFEKL (MHC class I epitope of OVA) was synthesized by the Toray Research Center .YSK12-C4, -19-(4-(dimethylamino)butyl) heptatriaconta-6,9,28,31-tetraen-19-ol, was synthesized as previously described39. The detail procedure is described in the Supplementary Information. E.G7-OVA cells, a murine lymphoma cell line EL4 expressing OVA, were purchased from the American Type Culture Collection  and were cultured in RPMI 1640 medium containing 50 μM 2-mercaptoethanol, 10 mM HEPES, 1 mM sodium pyruvate, 100 U/mL penicillin-streptomycin, 400 μg/mL G418 and 10% fetal bovine serum (FBS).BMDCs were prepared as reported previouslyFemale C57BL/6J mice (6–9 weeks old) were purchased from Japan SLC Inc.  and maintained under specific pathogen-free conditions. The use of the mice was approved by the Ethics of Pharmaceutical Science Animal Committee of Hokkaido University . All experiments were performed in accordance with National University Corporation Hokkaido University Regulations on Animal Experimentation.25. The detail procedure is described in the Supplementary Information. The lipid composition of the YSK12-MEND was YSK12-C4/cholesterol/ PEG2000-DMG (85/15/1 mol ratio). Although siIDO1 or siCtl were basically used, 10% of the siIDO1 was replaced to Cy5-siRNA when an analysis was done on cellular uptake24.The YSK12-MEND used in this study was prepared by the tert-butyl alcohol (t-BuOH) dilution procedure25. BMDCs (6.0 × 105 cells) were cultured for 2 h in 0.5 mL of serum-free OPTI-MEM I containing 10 ng/mL GM-CSF and 100 U/mL IFN-γ. The medium was then replaced with 0.5 mL of serum-free OPTI-MEM I containing 10 ng/mL GM-CSF and YSK12-MEND (siIDO1 or siCtl) at siRNA doses of 1, 10, and 20 nM, and the resulting BMDCs were incubated for 2 h. RNAiMAX and GeneSilencer reagents were mixed with siRNA solutions following the manufacturer’s instructions. The medium was then replaced with 0.5 mL of serum-free OPTI-MEM I containing 10 ng/mL of GM-CSF and the RNAiMAX or GeneSilencer preparations at siRNA doses of 10 and 20 nM. The BMDCs treated with RNAiMAX and GeneSilencer were incubated for 2 h and 4 h, respectively. After the incubation period, 0.5 mL of culture medium containing GM-CSF was added to the BMDCs, followed by a further incubation for 22 h. After the incubation, the BMDCs were collected and the mRNA expression was evaluated by qRT-PCR. The detail procedure is described in the Supplementary Information. IDO1 levels were calculated by the comparative CT method using GAPDH. The value for the non-treated cells was set to 1.The IDO1 gene silencing activity was evaluated at the mRNA level as reported previously with some modification25. BMDCs (6.0 × 105 cells) were cultured for 2 h in 0.5 mL of serum-free OPTI-MEM I containing 10 ng/mL of GM-CSF and 100 U/mL of IFN-γ. The medium was then replaced with 0.5 mL of serum-free OPTI-MEM I containing 10 ng/mL of GM-CSF and YSK12-MEND (Cy5-siRNA) at siRNA doses of 10 and 20 nM, and the resulting BMDCs were incubated for 2 h. RNAiMAX and GeneSilencer reagents were mixed with the siRNA solution (Cy5-siRNA) following the manufacturer’s instructions. The medium was then replaced with 0.5 mL of serum-free OPTI-MEM I containing 10 ng/mL of GM-CSF and the RNAiMAX or GeneSilencer preparations at siRNA doses of 10 and 20 nM. The BMDCs that had been treated with RNAiMAX and GeneSilencer were incubated for 2 h and 4 h, respectively. After the incubation period, the cells were collected and washed with 20 U/mL of heparin-PBS. The cells in a PBS containing 0.1% NaN3 and 0.5% bovine serum albumin (FACS buffer) were then analyzed by flow cytometry . The Kaluza software program (Beckman Coulter) was used for the data analysis. We normalized the obtained values of FI (GeoMean) by that for non-transfected BMDCs.The analysis of cellular uptake was performed as reported previously with some modification5 cells) were transfected with the YSK12-MEND (siIDO1 or siCtl) at a siRNA dose of 20 nM as described in the above section. The BMDCs were collected and then dispersed in FACS buffer. The BMDCs were treated with anti-mouse CD16/32 (10 μg/mL) for blocking. After washing, the BMDCs were stained with APC anti-mouse I-A/I-E, APC anti-mouse CD 40, APC anti-mouse CD80, APC anti-mouse CD86, PE anti-mouse CD11c or their isotype controls. The FI of the stained BMDCs was measured by flow cytometry . The data analysis was performed by SH800 software. We normalized the obtained values of FI (GeoMean) by that for non-treated BMDCs (without IFN-γ and antibodies).BMDCs (6.0 × 1015. BMDCs (6.0 × 105 cells) were cultured for 2 h in 0.5 mL of serum-free OPTI-MEM I containing 10 ng/mL of GM-CSF and 100 U/mL of IFN-γ. The medium was then replaced with 0.5 mL of serum-free OPTI-MEM I containing a 10 ng/mL solution of GM-CSF and the YSK12-MEND (siIDO1 or siCtl) at an siRNA dose of 20 nM, and the BMDCs were incubated for 2 h. After the 2 h incubation period, 0.5 mL of culture medium containing GM-CSF was trated to the BMDCs. After the 2 h incubation, the BMDCs were washed with culture medium and suspended in fresh culture medium, followed by a further incubation for 2 h. The BMDCs were then pulsed with the SIINFEKL peptide (750 nM) and OVA (50 µg/mL) for 1.5 h. After the incubation, the BMDCs were collected and washed with PBS. The mice were subcutaneously inoculated with 1 × 106 E.G7-OVA cells. On days 4, 8, 11 and 16, the mice were immunized by an injection of 3.0 × 105 mature BMDCs into the hind footpads. Tumor volume (mm3) = (major axis × minor axis2) × 0.52.The evaluation of antitumor was performed as reported previously with some modificationIn the tumor challenge experiment, the tumors were collected on day 18. Zirconia beads (mixture of 1 mm and 2 mm) and 600 μL of RNAiso Plus (Takara Bio Inc.) were added to the tumors (25 mg). The tumors were homogenized with a Micro Smash homogenizer . After centrifugation, 350 µL of supernatant was collected and mixed with 350 µL of ethanol. The RNA was isolated with a Direct-zol RNA MiniPrep  according the manufacturer’s instructions. The total RNA was then reverse transcribed using a PrimeScript RT reagent Kit with an oligo-dT primer and random 6 mers. Quantitative PCR was carried out on a Light Cycler 480 System in a reaction mixture containing cDNA, with appropriate pairs of primers and the THUNDERBIRD SYBR qPCR Mix. The mRNA levels of Foxp3 and CD25 were calculated by the comparative CT method using β-glucuronidase (Gusb) as an endogenous gene. The values for the PBS treated mice were set to 1. The following primer pairs were used: Foxp3: 5′-TGCAGGGCAGCTAGGTACTTG-3′ (forward); 5′-TCGGAGATCCCCTTTGTCTTATC-3′ (reverse); CD25: 5′-AACCATAGTACCCAGTTGTCGG-3′ (forward); 5′-TCCTAAGCAACGCATATAGACCA-3′ (reverse). Gusb: 5′-GTGGTATGAACGGGAAGCAAT-3′ (forward); 5′-AACTGCATAATAATGGGCACTGT-3′ (reverse).Comparisons between the two treatments were performed by the unpaired t-test. Statistical analyses of multiple comparisons were performed by one-way ANOVA, followed by the Tukey-Kramer test Fig. . A P-valSupplementary Information


Mesodinium rubrum located at the ice-water interface of newly formed pack ice of the high Arctic in early spring. These planktonic ciliates are not able to attach to the ice. Based on observations and theory of fluid dynamics, we propose that convection caused by brine rejection in growing sea ice enabled M. rubrum to bloom at the ice-water interface despite the relative flow between water and ice. We argue that red tides of M. rubrum are more likely to occur under the thinning Arctic sea ice regime.In the Arctic Ocean ice algae constitute a key ecosystem component and the ice algal spring bloom a critical event in the annual production cycle. The bulk of ice algal biomass is usually found in the bottom few cm of the sea ice and dominated by pennate diatoms attached to the ice matrix. Here we report a red tide of the phototrophic ciliate  During the ice algal spring bloom the highest biomass is usually found at the bottom 2–3 cm of sea ice in the interstitial environment of the skeletal layer forming as the ice grows. Here the cumulative light energy input is relatively high and nutrients are supplied from the underlying water6. Previously proposed physical mechanisms for colonization of the skeletal layer are harvesting or scavenging by frazil ice crystals, waves that push algae into the ice7, and the skeletal layer acting as a comb sieving algae from the water5.In the high Arctic the relative contribution of ice algae to total primary production can be up to 60% because the snow covered perennial pack ice cover efficiently shades the under-ice water column, thus limiting phytoplankton growth8. From the benthic environment it is known that shear inhibits the colonization of surfaces by algae10. Typically the algae colonizing benthic surfaces can attach to the substrate and pennate diatoms are often dominating11. The same is true for sea ice13. Pennate diatoms excrete mucilage that enables them to adhere to and, in the case of raphe-bearing pennate diatoms, to move on the ice surface16. Motile algae without the capacity to adhere to the sea ice matrix are prone to displacement, presumably limiting biomass accumulation at the ice-water interface.Between the ice and the water column there is almost always a relative motion, due to water currents, and in the case of pack ice, wind-driven movement of the ice. Momentum transfer creates a boundary layer with decreasing velocity but increasing shear towards the ice under-surface, with laminar flow closest to the ice and turbulent flow outside17, we observed a dense bloom of the phototrophic ciliate Mesodinium rubrum (aka Myrionecta rubra) located at the ice-water interface of growing young ice (YI), in a lead that opened and refroze in late April and early May 2015. The bloom of M. rubrum at the ice-water interface can be likened to a red tide, well known for this species at lower latitudes18. To our knowledge this is the first observation of an ice-associated red tide of M. rubrum in the Arctic Ocean. M. rubrum is a motile planktonic species that, unlike e.g. diatoms and surface associated ciliates, cannot attach to the ice matrix20. Then, how can these ciliates remain stationary at the ice-water interface despite the flow? We calculated the theoretical thickness of the laminar boundary layer with the observed relative velocity and concluded that it is unlikely that the ciliates could reside within it. However, the red tide of M. rubrum coincided exactly with the period of ice growth, and we propose that in growing YI convection resulting from brine rejection compensated by seawater inflow interrupted the laminar boundary layer and allowed M. rubrum to stay in the ice-water interface as long as the ice was growing. The proposed hydrodynamic model provides a mechanistic explanation for the occurrence of blooms of motile algae below drifting pack ice.During the Norwegian young sea ice drift study (N-ICE2015) north of SvalbardLance drifted repeatedly with pack ice floes from about 83°N northwest of Svalbard south or southwestwards towards the ice edge at around 81°N17. We refer to the four ice drifts as Floes 1 to 4. This study is mainly from the drift of Floe 3 from 20 April to 6 June  in a refrozen lead along a transect of five ice stations  or multiyear ice (MYI). The thick ice had a modal ice thickness of 1.46 ± 0.66 m and snow thickness of 0.39 ± 0.21 m according to a local area survey23. The loss in total thickness of snow and ice in the period from 27 April to 4 June was 6 and 3 cm per 30 days for MYI and FYI, respectively23, indicating minor changes in the ice pack surrounding the refrozen lead. Under the FYI and MYI the irradiance was 1–10 µmol photons m−2 s−1, and under YI on average 114 µmol photons m−2 s−1 22. The mixed layer depth of the water column below the ice was approximately 50 m throughout the study period24. During this study nutrients  were always available in excess in the under-ice water21.The observations reported here are from the N-ICE2015 expedition lasting from January to June 2015, when R/V Mesodinium rubrum was detected in young ice (YI) of the refrozen lead throughout the study period with abundance in the range of 0.3 to 15.7 × 106 cells m−2 (Table 6 cells m−2) was observed in slurp gun samples taken by divers from the ice-water interface  in the bottom 10 cm of YI of the refrozen lead in the period 4 to 20 May, and then a rapid, two orders of magnitude decline after 20 May  standing stock, a proxy for algal biomass, was measured at the ice-water interface of the refrozen lead with values in the range 0.9–15 mg m−2 for the period 6–14 May. The Chl a concentration in these slurp samples was in the range 7–117 mg m−3. In the same period, the Chl a standing stock in the ice cores was in the range of 0.09–1 mg m−2. The highest Chl a standing stock measured in ice was around 3 mg m−2 in the bottom 10 cm of the refrozen lead in late May and early June  layer of the YI interface equals 4.3% of the total integrated amount found in the water column from 0 to 25 m depth.The highest chlorophyll a  than in the YI cores (0.004 and 0.08 mg m−2 with a peak of 0.4 mg m−2 on 20 May). In the FYI and MYI, the standing stocks of alloxanthin were even lower, in the range 0.001–0.008 mg m−2 (Table a ratio (mg: mg) was in the range of 0.01–0.03 in YI, except for ratios of 0.07–0.13 coinciding with Chl a peaks on 4, 10 and 20 May13, and up to 0.36 at the ice-water interface. In the water column alloxanthin standing stocks increased from winter levels of 0.02–0.04 mg m−2 to approximately 0.1 mg m−2 in the period 11–18 May  measured in slurp samples from the ice-water interface of the refrozen lead on 5–14 May was in the range 0.40–0.64 (Table −2 s−1)−1, maximum relative electron transfer rate (rETRmax) = 72–198 (no unit), saturation irradiance (Ek) = rETRmax/α = 153–549 µmol photons m−2 s−1 , whereas during events of stronger free-stream velocities . In Supplementary Material Section The average relative velocity between ice and water was 11 cm s−1 Fig. . Figure s−1 Fig. , the thiage Fig. , the thiies Fig. , the thia m−3 we measured in the slurp samples from the YI interface layer is 14–234 times higher than the concentration in the water column (<0.5 mg Chl a m−3), which was at the level of non-bloom concentrations reported from the North Atlantic27. The interface bloom can be likened to the red tides of M. rubrum often observed at lower latitudes, where the Chl a concentration can be >100 mg m−3 and abundance up to 106 cells L−1 28. To our knowledge, ours is the first observation of a pack ice associated red water bloom. The only published observation of a red tide in the Arctic Ocean is from ice-free, coastal waters near Barrow, Alaska in September 1968, caused by an unidentified ciliate similar to, but not identical with M. rubrum29. The abundance in the bottom 10 cm of YI (0.3 to 15.7 × 106 cells m−2) is comparable to some other observations. Up to 1.6 × 106 cells m−2 of M. rubrum was observed in the bottom 2–4 cm of 30–40 cm thick FYI in the Saroma-ko lagoon in Hokkaido, with an integrated abundance in the water column under the ice from 0 to 1 m depth of 3.4 × 106 cells m−2 30. Likewise, when M. rubrum was observed at abundance 2 × 105 cells m−2 in the bottom 2–4 cm of 1.5–2 m thick FYI in the Canadian Arctic, the average abundance in the water column below the ice down to 8 m was 0.14 × 103 cells L−1 31. The maximum abundance we measured in the YI ice-water interface (211 × 106 cells m−2) was considerably higher than these observations.The 7–117 mg Chl M. rubrum cells are known to be fragile and difficult to preserve. The mix of glutaraldehyde and formaldehyde used during the N-ICE campaign was chosen in order to preserve the highest possible fraction of the entire protist community, but might not be the best method to preserve M. rubrum18. The high abundance of chloroplasts originating in M. rubrum in the ice core samples  is similar to the irradiance they grow under. We measured Ek > 153 µmol photons m−2 s−1, indicating they were growing stationary at the YI ice-water interface. This Ek is similar to what Stoecker et al.36 found for M. rubrum in temperate waters, and what McMinn and Hegseth37 found for surface phytoplankton in the Arctic Ocean north of Svalbard in spring.According to the quantum yield of fluorescence (0.40 to 0.64) the protists, mainly rea Fig. . The M. M. rubrum cells actively position themselves under the thin ice, or is there some external physical mechanism keeping them there? The swimming speed of M. rubrum is approximately 0.16 mm s−1 19, whereas the average relative velocity of ice vs. water was 0.11 m s−1  and helps M. rubrum cells to remain in the skeletal layer, maybe assisted by their own upwards, phototactic swimming .The regional sampling showed similar abundances in a larger area surrounding R/V May Fig. , suggestkm2 Fig. , which p25 can promote ephemeral blooms of M. rubrum below growing young ice. It is important to improve our understanding of the mechanisms enabling ice-associated blooms of different algal taxa. Shifts in species composition at the base of the ice-associated ecosystem is an indicator of change, and are likely to have cascading effects on the Arctic marine food web and the biological carbon pump of the Arctic Ocean.The ongoing regime shift towards a thinner, more dynamic ice cover in the Arctic Ocean, with more lead formation24. The current speed and direction at 23 m depth were used to calculate the current relative to the ice floe based on ship navigation data. The relative current speed measured between the water column and the sea ice was in the range 0–0.3 m s−1, with an average of 0.11 m s−1  from Teledyne RD Instruments was used to measure current speed and direction below the ice. The profiles were hourly-averaged in 8-m vertical bins and the first bin was centered at 23 ms−1 Fig. . The appa (Chl a), pigment composition and protist counts were collected with a rosette water sampler with 8 L Niskin bottles deployed from the ship or with 3.5 L Niskin bottles on a rosette deployed from the ice. Samples were taken at 5, 25, 50 and 100 m depths from the ship, and from 2, 5 and 15 m with the on-ice system. During a regional sampling campaign by helicopter on 19 and 20 May water samples were taken manually with a Limnos water collection bottle closed with a messenger (Limnos. pl) at 5, 15 and 25 m depth. To obtain depth integrated values of Chl a or abundance we used the trapezoid method. Because we had no measurements from 0 m we set the values to equal those at 5 m depth.Seawater samples for chlorophyll Three ice-tethered sediment traps (KC Denmark) were deployed on a rope stretched under the YI horizontally at 1 m depth. In addition, four sediment traps were deployed vertically at 5, 25, 50, and 100 m depth, respectively, along a mooring attached to the ice. The deployment time was between 36 and 72 h, usually 48 h. To avoid loosing sample water from the traps during deployment and recovery, the trap cylinders were filled with filtered seawater, made hypersaline (i.e. more dense) by adding sodium chloride, before deployment. Each trap had two cylinders with internal diameter 7.2 cm and height 45 cm, with no baffle at the top. At sampling the water from both cylinders were combined into one sample. Copepods and other zooplankton were removed before taking samples for algal taxonomy. Sinking flux for protists was calculated from cell concentration in the traps, trap volume and area, and trap deployment time.et al.31.Samples from the sea ice were taken with 9 and 14 cm diameter ice corers . The cores were cut into 10 or 20 cm sections, put in cleaned opaque plastic containers and melted during 18–24 hours at room temperature without seawater buffer on board the ship, according to Rintala Samples from the ice-water interface under the refrozen lead were taken by scuba divers using a modified 3.5 L Trident® suction gun (slurp gun). The front nozzle was oblique so that it was possible to fill the gun while moving it along the undersurface of the sea ice. The surface area sampled was 5 × 54 cm for a full slurp gun and this area was used to transform cells per volume in the sample to cells per area.53. In most cases 50 ml of the samples was settled, in some cases 10 ml. 20, 40 and 60X magnification was used and the number of view fields counted varied to obtain a minimum of 50 cells of the dominating species, i.e., with a maximum count error of ±28% according to Edler and Elbrächter54. Carbon biomass was determined by calculating volume from cell size55, which was converted to carbon using published conversion factors56. With this method and maximal magnification of 600X we detected mainly protists with cell diameter >2 µm.For protist taxonomy analysis and cell counts, 190 mL from Niskin bottles, slurp gun, sediment traps, or melted ice cores were transferred into 200 mL brown glass bottles and fixed with an aldehyde mixture consisting of glutaraldehyde at a final concentration of 0.1% and hexamethylenetetramine-buffered formaldehyde at a final concentration of 1% (vol:vol). The samples were stored dark and cool until analysis. Protists were counted with an inverted Nikon Ti-U light microscope  using the sedimentation chamber method of Utermöhla were collected on 25 mm diameter GF/F filters . The volume filtered was noted. Chl a was extracted in 100% methanol for 12 h at 5 °C in the dark and subsequently measured using a Turner Fluorometer 10-AU . Phaeopigments were measured by acidifying the sample with 5% HCl before measuring the fluorescence57. Samples to measure algal pigment composition were collected by filtering 10–1000 mL of sample through 25 mm GF/F filters, which were snap frozen in liquid nitrogen and then kept frozen at −80 °C until analysis. After an extraction step the pigments were measured using a Waters photodiode array detector (2996), Waters fluorescence detector (2475), and the EMPOWER software. The pigments were separated by reverse-phase high-performance liquid chromatography (HPLC) in a VARIAN Microsorb-MV3 C8 column (4.6 × 100 mm) using HPLC-grade solvents (Merck). For further details see Tran et al.58. Chl a was measured by both Fluorometer and HPLC for most samples in this study. A linear regression of all data from YI cores (n = 87) gave the relationship Chl aHPLC = 0.65 Chl aFluorometer + 0.11, R2 = 0.83. All our reported Chl a concentrations were measured by fluorometer, whereas all alloxanthin: Chl a ratios were calculated from alloxanthin and Chl a measured by HPLC.Samples for Chl M. rubrum in samples from the refrozen lead ice-water interface were assessed using in vivo Chl a fluorescence kinetics measured with a Pulse Amplitude Modulation (PAM) fluorometer . Samples were kept in a fridge with temperature in the range 1–2 °C and dark-acclimated for 30 min prior to measurement. The maximum quantum yield of fluorescence of photosystem II (ΦPSIImax) was measured with the saturation pulse method31. Rapid Light Curves (RLC) in which the quantum yield of fluorescence in the light (ΦPSII) was measured by illuminating the sample with actinic light increasing stepwise from 1 to 900 µmol photons m−2 s−1 in 13 steps at 20-second intervals, were used to assess the light response of the algae. The first measurement was after dark-acclimation, i.e. ΦPSIImax. Relative electron transfer rate (rETR) was calculated by ΦPSII × E, where E is the actinic irradiance. The photosynthesis-light function of Webb et al.59 was fitted to the rETR data as a function of the incident actinic light:max is the curve asymptote, i.e. the maximal rETR. We did not observe inhibition of rETR at high irradiance so we did not add an inhibition term to the equation.The physiological status and light response of the photosynthetic apparatus of 8: (1) a laminar, molecular sub-layer (~0–1 mm thick) close to the sea ice-ocean interface, where the velocity varies linearly with depth; (2) a logarithmic turbulent layer (~1–3 m thick) below the laminar sub-layer, with constant stress and where the velocity varies logarithmically with depth; (3) a turbulent, thicker outer layer (~10 m thick), where the velocity is affected by the Coriolis effect. In this study we focus on the first two layers closest to the ice-water interface: the laminar sub-layer and the logarithmic turbulent layer. The surface shear stress in the ice-water interface60 is defined as:u* is the frictional or shear velocity at the boundary layer, which provides a scale for turbulence strength and for the laminar boundary layer thickness. The surface stress τ in the vicinity of the sea ice, which is dominated by viscous  forces, may also be given by White61:µ is the dynamic viscosity of seawater, which at 0 °C is µ = 1.8 × 10–2 g cm−1 s−1. Additionally, the magnitude of the surface stress is related to the drag force of the geostrophic fluid under a boundary  as:Cd is the dimensionless geostrophic drag coefficient, taken here as 5.5 × 10−3 and ug is the geostrophic flow away from the boundary, also referred to as the free stream velocity relative to the sea ice velocity. From  varies with depth as:with the thickness of the laminar sub-layer beingz = δlsl to z = δsl ~ 1–3 m), turbulent forces become more important than viscous forces. This log layer follows the “law of the wall”, where the velocity varies logarithmically with depth  5 cm s−1; (b) 10 cm s−1 ; (c) 20 cm s−1 and (d) 30 cm s−1. Using Eqs * and the thickness of the laminar sub-layer δlsl. We then solve for the velocity profiles both at the laminar sub-layer (linear) and at the logarithmic layer.Right below the laminar sub-layer, in the logarithmic layer (i.e., from s−1 Fig. . We starSupplementary material for: A red tide in the pack ice of the Arctic Ocean