Marine geological data show that the West Antarctic Ice Sheet (WAIS) advanced to the eastern Ross Sea shelf edge during the Last Glacial Maximum (LGM) and eventually retreated ~1000 km to the current grounding-line position on the inner shelf. During the early deglacial, the WAIS deposited a voluminous stack of overlapping grounding zone wedges (GZWs) on the outer shelf of the Whales Deep Basin. The large sediment volume of the GZW cluster suggests that the grounding-line position of the paleo-Bindschadler Ice Stream was relatively stationary for a significant time interval. We used an upper bound estimate of paleo-sediment flux to investigate the lower bound duration over which the ice stream would have deposited sediment to account for the GZW volume. Our calculations show that the cluster represents more than three millennia of ice-stream sedimentation. This long duration grounding was probably facilitated by rapid GZW growth. The subsequent punctuated large-distance (~200 km) grounding-line retreat may have been a highly non-linear ice sheet response to relatively continuous external forcing such as gradual climate warming or sea-level rise. These findings indicate that reliable predictions of future WAIS retreat may require incorporation of realistic calculations of sediment erosion, transport and deposition. Hence, the interval of time when ice sheet paused at any one location during the ongoing post-LGM retreat remains unknown.Sediment from shallow-penetration piston and kasten cores recovered from the Ross Sea continental shelf grade upwards from tills deposited by or in proximity to grounded ice to an overlying condensed section (a few tens of centimeters thickness) of post-glacial sediment deposited after the retreat of grounded ice7  for the Whales Deep Basin paleo-ice-stream trough. The estimate of paleo sediment yield was applied to the larger drainage basin area that existed when the WAIS was grounded on the outer continental shelf  for the Whales Deep paleo ice stream trough using Equation  for the Whales Deep paleo ice stream trough using Equation  to estimate the duration of the outer-shelf grounding events using Equation (d is duration in years (a), vs is CGZW sediment volume (in m3), and QP is the Whales Deep paleo-ice-stream sediment flux (in m3a−1).In the third part of our study, we used the paleo sediment flux  over the larger paleo drainage area results in a paleo sediment flux, QP, of 1.42 × 108 m3a−1  are primarily dependent on the glacierization mode 23. The upper-most reaches are deeply excavated and exhibit high relief , the outer-shelf CGZW in Whales Deep is the largest system yet mapped and thus likely records a relatively prolonged grounding.The outer shelf CGZW volume is greater than the large GZWs in Joides, Drygalski and Glomar Challenger Basins that have been seismically mapped in the western and central Ross embayment4. Stratigraphic superposition requires that GZW5b is younger than GZW5a, the wedge of sediment that underlies the outer shelf and upper slope  experiences fast plug-like flow34. In addition to sediment transport in a deforming basal till layer, recent studies indicate that a significant volume of sediment could also be transported to the grounding line in basal ice layers35. Melting at the grounding line demonstrates that a significant volume of sediment transported in basal ice layers could be deposited at the grounding line36. Hence, the paleo sediment flux across the grounding line depends on the combined contribution of deformation till and sediment concentrated in basal ice layers. We assume that the relatively high erosion rate of 0.625 mma−1 used here reflects an upper bound input of all sedimentary material to the CGZW, whether transported to the paleo-grounding line subglacially or in the basal ice. The width of the paleo Bindschadler Ice Stream on the outer shelf is ~100,000 m  and net velocity . Early studies emphasized deforming till layers, which were proposed to range in thickness from 2 to 15 m. Alley −1) for the early deglacial is consistent with the view that 1) the overall mode of glacierization did not change significantly between the early deglacial and the modern and that 2) the early deglacial flux should be slightly higher22 relative to that estimated by Alley et al.19. Our use of a 0.625 mma−1 yield as a representative paleo yield for the early deglacial is also supported by a comparison to paleo sediment yields estimated for the similarly wide and long ice streams that drained large-drainage basins for the marine-based ice sheet that formerly covered Barents and North Seas. In those areas, erosion rates averaged ~1 mma−1 after the peak of the LGM37. Our paleo flux estimate for the paleo Bindschadler Ice Stream (1.4 × 108 m3a−1) is of the same order but slightly lower than that for the Norwegian Channel Ice Stream37. At that time, grounded ice advanced to the North Sea shelf edge38, the Norwegian Channel drained an area from 6.1 to 7.8 × 1011 m2. Hence, the greater sediment flux values for the Norwegian Channel ice stream was due to a combination of a larger drainage area and a higher average yield . Even higher yields of 2.4 mma−1 were associated with the Storfjorden and Bear Island ice streams in the middle Pleistocene14. Those high yields were attributed to the onset of large amplitude oscillations of grounding line across previously unglaciated landscapes mantled by unconsolidated sediment cover. Modern yields from small temperate Alaskan valley glaciers and those in the Swiss Alps are the highest reported erosion rates (5–10 mma−1) but these rates are due to high relief, erodible rock types, and highly fractured substrates in the presence of voluminous melt water15. We do not favor the view that paleo sediment yields could have exceeded 1 mma−1 in the Whales Deep drainage area because such high values are more typical for temperate mountain glaciers flowing over high relief and fractured substrates in settings such as Alaska39 whereas the WAIS drainage area is relatively flat and presumably consolidated Cenozoic rock40. Relatively low long-term rates of sub-ice stream erosion in the Ross Sea sector of WAIS are also supported by the fact that these ice streams are associated with troughs that have relatively low relief. In contrast, the very high erosion rates beneath temperate mountain glaciers produce valleys with topographic relief that is one to two orders of magnitude greater than observed in our study region.Our upper bound estimate for the paleo sediment yield  created by the orientation of the Hayes and Houtz banks. At the Whales Deep outer shelf, the overall >100 m aggradation of sediment at the grounding line is consistent with previous conjecture that sedimentation at the grounding line itself exerts a control on grounding line stability46. Hence, the CGZW may be an example of a situation where such depositional processes created and maintained a pinning point, which stabilized the regional grounding line position for thousands of years.There is no definitive explanation as to why the WAIS grounding line paused so long on the outer shelf in the Whales Deep Basin. However, neither the duration nor the available age control is sufficiently resolved to establish a correlation to post-LGM sea level changes or other possible mechanisms47. The long grounding is also significant with respect to how such a long interval with a stationary grounding line was followed by geologically instantaneous long distance retreat of grounded ice from the outer shelf to Roosevelt Island. The rapid retreat phase may represent compensation for the fact that GZW growth phase makes an ice stream grounding line stable despite climate and sea level forcings. Once those factors make grounding at the GZW untenable, then the resulting retreat to a new stable position is large and rapid. Although the exact radiometric timing and duration is yet to be determined, the data clearly highlight an important paradoxical duality to the WAIS dynamics with long intervals of relatively stationary grounding lines followed by rapid return of grounded ice to the global ocean.A 3700-year outer shelf grounding is significant because it provides perspective as to the possible durations of past and modern stationary grounding line positions and the presumably stable ice sheet mass balance. In comparison, GZWs elsewhere on the Antarctic margins with smaller volumes have been inferred to represent significantly shorter duration grounding events ranging from a few decades to slightly longer than a millenniumOur estimate of sediment flux for the paleo Bindschadler Ice Stream predicts that the CGZW would have taken on the order of 3700 years to deposit. The absence of any seismically resolvable GZWs south of the bathymetric saddle indicates that a large distance retreat of the grounding line from the outer shelf to the latitude of Roosevelt Island occurred in a geologic instant. The long-duration grounding followed by an abrupt large-distance grounding line retreat may have resulted from a highly non-linear ice sheet response to relatively continuous external forcing such as gradual climate warming or sea level rise. Our findings indicate that reliable predictions of future WAIS retreat may require incorporation of realistic calculations of sediment erosion, transport and deposition.Supplemental Figure


The number of ice cover days has decreased considerably (~28days/century) mainly due to an increase in the winter mean temperature. In a long-term context, based on documentary evidences, we show that the ice cover occurrence rate was relatively small throughout the Medieval Warm Period (MWP), while the highest occurrence rates were found during the Maunder Minimum and Dalton Minimum periods. We conclude that the river ice regime can be used as a proxy for the winter temperature over the analyzed region and as an indicator of climate-change related impacts.Many of the world’s largest rivers in the extra tropics are covered with ice during the cold season, and in the Northern Hemisphere approximately 60% of the rivers experience significant seasonal effects of river ice. Here we present an observational data set of the ice cover regime for the lower part of the Danube River which spans over the period 1837–2016, and its the longest one on record over this area. The results in this study emphasize the strong impact of climate change on the occurrence of ice regime especially in the second part of the 20 As such, changes in river ice cover can be seen as an indication of changes in the climate forcing factors . As the global warming is anticipated to continue4, the continuous monitoring of lake and river ice could provide an early indicator of predicted global and regional warming. Due to the fact that ice record integrates climatic conditions during the late autumn/winter/spring months, when most of the warming is observed5, long-term observation of river ice can be extremely valuable. Long-term series of ice phenology have been employed successfully as indicators of past regional climate in Japan6, Finland8, Switzerland10, Canada13, Hungary15, as well as at hemispheric level16.The formation of ice on lakes and rivers is a complex phenomenon that involves many meteorological, hydrological and physiographical properties of the catchment area. The meteorological and hydrological factors tend to vary both in time in space, the same being true for the ice conditions. Linking the occurrence of ice on lake and rives to climatic forcing might be a complex task to fulfill, however this task is simplified considerably by the fact that air temperature is the dominant factor driving the ice phenology18. In addition to the natural variability, anthropogenic influences may also contribute to changes in the lake and river ice phenology, by alternating the large-scale atmospheric circulation, or alternations in land-use and human development16. Human interference in the river basin can lead to significant changes in ice conditions, especially by regulating the river flow and the construction of hydro-power stations.At European level, lake and river ice cover has been associated with local weather at seasonal scales, such as temperature and precipitation, and large-scale teleconnection patterns, like the North Atlantic Oscillation and El Nino-Southern Oscillation19. The record has been collected just over the lower part of the Danube River at Tulcea station . This is the first long-term record of ice cover duration over this area, which extends back ~180 years. The river ice record was collected starting 1836 by the Danube River Commissionion Fig. . The ice2. In the upper course, the Danube regime is determined by its alpine tributaries. The middle and lower course of the river stand under the influence of Drava and Sava rivers. Because of its large extension from west to east, and diverse topography 22.The Danube River Basin is the second largest river basin in Europe, after the Volga River, covering an area of 801 463 kmphy Fig. , the DanThe temperature regime in the lower part of the Danube River, close to the Danube Delta, can be described by the data recorded at Sulina, Bucuresti and Calarasi meteorological stations. We choose these particular stations due to their location in the near proximity of our area of interest and their lengthy time span: Sulina ; depth, slope and water speed (hydraulic factors) and discharge . Due to its location, the Danube catchment area is under the influence of different air masses, which present a high interannual variability. Hence, the ice regime presents an increased variability in the freeze-up date, break-up date and ice cover duration throughout its catchment area. Over the Romanian part, between Orsova and Cetate gauging stations   Fig. . Over thays Fig. . One of ays Fig. .Figure 2To test the possible trends, in the occurrence rates and the years of change in the mean, we have applied different statistical tests (see Methods) to our ice cover time series. First we have separated the time series in three different magnitude classes: a) class 1 (1 ≤ ice cover duration ≤60 days); b) class 2 (60 < ice cover duration ≤90 days) and c) class 3 (ice cover duration >90 days). Figure 26, we show that a significant jump, towards more positive temperatures, is found in 1947 at Bucuresti and Sulina stations. For the ice cover duration, both tests indicate a jump in the mean, towards less ice covered winters, at ~1943. The fact that the year of change in both winter mean temperature and ice cover duration are relatively close, could be an indication that the jump in the winter mean temperature was the driving factor of the sharp decrease in the ice covered data, especially in the second part of the 20th century.Over the analyzed period, both the winter mean temperature at Bucuresti and Sulina station as well as the ice cover duration data show significant trends and close years for the change in the mean: the winter mean temperature shows a positive and significant trend  during LIA. They also show that the freezing of these two rivers had an abrupt drop in the occurrence rate throughout the 20th century, which they related mainly with regional warming. Some of the freezing events, in the lower part of the Danube River, during LIA, were so extreme that the freezing has extended from the Black Sea up to the Bosphorus 30.For collecting information on ice covered winter, over our sector of interest, throughout the historical period, we relied mainly on old book entries and a collection of different sources Table . Based o31 at European level. The relationship between the ice cover duration and winter mean temperature was analyzed by means of spatial correlation map .The spatial relationship between the river ice duration and winter mean temperature was analyzed by employing a reconstructed temperature data setmap Fig.  as well map Fig. . The spamap Fig.  we have map Fig. , for difFigure 34. As such, due to its significant and stable relationship with the winter mean temperature, the ice cover duration record in the lower part of the Danube River has the potential to provide a powerful proxy temperature over the eastern part of Europe.Before 1837, we have indication just regarding the occurrence of ice cover in the lower part of the Danube River, but no indication regarding the duration. Nevertheless, the coldest winters (before 1837) identified in the winter mean temperature index have all a correspondent in the ice cover occurrence  is observed for the minimum winter discharge (the lowest daily discharge throughout the winter months (December-January-February)), in the second part of the 20th century  shows a significant decreasing trend . In order to be able to infer the large-scale atmospheric drivers of the ice regime we have computed the composite map of the geopotential height and wind component at 500 mb, for the years when the ice cover duration was >30 days/winter .Ice covered winters are also associated with a higher frequency of atmospheric blocking situations over the British Isles extending up to the Scandinavian Peninsula Fig. . Atmosph12. Both the temporal and the spatial resolution are a problem for a hemispheric or continental evaluation of river ice conditions. The most comprehensive study, for the whole Northern Hemisphere, was published by Magnusson et al.16. In their study, Magnusson et al.16 showed that the freeze-up (break-up) dates have became 5.7 days/100 yrs later (6.3 days/100 yrs earlier). The rates of change were noted to correspond to an increase in the winter mean temperature by ~1.2 °C/100 yrs. Over the eastern part of Europe there are just a limited number of studies regarding the analysis of freshwater ice regime41. These studies are focused on the Danube River41, Drava River15 and lake Balaton14. For example, it has been shown that the freeze-up and break-up dates, for Danube River at Budapest station, have shifted later by 9–27 days/100 yrs and earlier by 7–13 days/100 yrs, respectively.Records of ice cover conditions are collected especially in the cold-regions countries , but for different purposes. Although river ice conditions have a significant importance for hydrology , large-scale analyses on this particular topic are almost non-existentth century. This abrupt drop in the ice cover occurrence, in the second part of 20th century, has been observed also at Nagymaros, Mohacs and Komarom stations   Figure . The shi) Figure . Between) Figure  show a sy Figure . The onl4. Across many temperate areas the warming is typically greater in winter and spring43. Anthropogenic climate change is also expected to intensify the hydrological cycle44. As a consequence, hydrological flow regimes will be modified by climate change, through alterations in precipitation, temperature, snow and ice cover. Alongside with this changes, here we show that the ice cover data, from the lower part of Danube River, revels a significant decreasing trend, after 1950’s, in the occurrence rate of ice covered winters. Over the last ~60 years, there were just ten winters when river ice cover occurred. Before 1950’s ice cover was occurring almost every winter, with small exceptions. This significant decreasing trend in the number of ice covered winters follows the general NH pattern. River across the NH have experienced similar trends regarding the length of the ice cover duration47. In terms of freeze-up and break-up dates, our time series does not follow the general NH pattern. At NH scale, there is an overall trend towards later ice freeze (~0.57 days/decade) and earlier ice breakup (~0.63 days/decade)6. For our region, no significant trend/change was found in the freeze-up and break-up dates  and the significant decrease in the occurrence rate of cold winters Figure . We have50.To have a clear picture regarding the drivers of the significant decrease in the occurrence of ice covered winters, after the beginning of 1950’s, we have first tested if there were significant changes in the atmospheric circulation. By performing a trend analysis and cluster analysis (not shown), we found that no significant changes have occurred in the large-scale atmospheric circulation. The dipole-like structure Fig.  which fa51, the Silesian Upland (southern Poland)52 and the Danube River at Budapest station41. Between 1837–1950, a mean winter temperature of −0.54 °C was needed to induce ice cover occurrence at Tulcea station, while a mean winter temperature of −1.05 °C was needed after the beginning of the 1950’s . Anthropogenic influences on the occurrence of ice regime, for different water bodies, have been already observed for the Lower Vistulas Figure . This suIn a long-term context, here we show that the ice cover occurrence rate follows the variability of winter mean temperature throughout the MWP and LIA. Warmer periods, like the MWP, are characterized by a reduced ice cover occurrence rate, while colder periods, like LIA, are characterized by higher ice cover occurrence rate. As such, historical and observational data regarding the occurrence rate of ice cover could provide us with valuable information on past and present changes in the large-scale climate. The high correlation between the number of ice cover days and the winter temperature over the central and eastern part of Europe, reveals that the ice regime can be used as a proxy for the winter temperature over this region.53. The projected median changes of the FD simulated in the CMIP5 ensemble runs54, for the RCP8.5 scenario (worst-case scenario), are shown in Figure n < 0 °C) is obvious at hemispheric scale. The decrease in the number of FD is particularly strong over the western part of North America and the central and eastern part of Europe. In the RCP8.5 scenario the reduction of FD, over the period 2051–2100 relative to the period 1961–1990, is up to ~60days/year in the central and eastern part of Europe. Overimposed on these changes, an increase in the winter mean air temperature in the range of ~2.5 to 5.5 °C (RCP8.5) is projected until the end of the 21st century, over the eastern part of Europe55 together with an increase in the surface water temperature of ~1 °C in the lower part of the Danube River56. Under these conditions, one expects that by the end of the 21st century the ice regime in the lower part of the Danube River will be drastically reduced, due to the fact that, over the analyzed region, river ice cover appears just when the winter mean temperature drops bellow 0 °C. Moreover, winter with ice cover duration >60 days/winter occur just for winter mean temperatures < −2 °C  is extracted from the Hadley Center Sea Surface Temperature data (HadSST)59. This dataset covers the period 1871–2016 and has a spatial resolution of 2° × 2°.For the Northern Hemisphere large-scale atmospheric circulation, we use the daily and monthly means of geopotential height at 500 mb level, as well as the zonal and meridional wind at the same level, from the twentieth century reanalysis project on a 2° × 2° grid60:Tn is the timing of the nth ice event with unit of year; m is the number of ice events occurrence; K is the Gaussian kernel function and h is the width of the kernel function (h = 30 years). Confidence intervals (90%) around λ(t) were determined using a bootstrapped technique: N simulated ice events were drawn from Tn with replacement and simulated λ calculated. This procedure was repeated 5000 times and a percentile-t confidence band was calculated. The trends in the occurrence rate were confirmed using the Cox and Lewis statistical test61.The occurrence rate of the time-dependent extreme events can be computed as63 and Spearman’s Rho, which are less sensitive to outliers than parametric statistics, were used. To avoid the influence of serial persistence on M-K test results, the modified M-K (MMK) trend test was used, using the computation algorithm discussed by Hamed and Rao64.The rank-based non-parametric Mann-Kendall (M-K) test68. The basic idea of this procedure is to identify regions with stable teleconnections between two variables. The ice cover data has been correlated with the winter mean air temperature, in a moving window of 31 years. The results remain qualitatively the same if the length of the moving window varies between 15 to 35 years. The statistical significance of the correlation coefficient is tested using a Student t-test. The correlation is considered to be stable for those grid-points where the ice cover data and winter mean temperature are significantly correlated at 95%, 90%, 85% and 80% level for more than 80% of the 31-year windows, covering the period 1837–2000. The regions where correlation is positive and stable will be represented as dark red (95%), red (90%), orange (85%) and yellow (80%) on a global map. The regions where correlation is negative and stable will be represented as dark blue (95%), blue (90%), green (85%) and light green (80%) . This data set was extracted from the NCEP/NCAR reanalysis data58 for the 1851–2014 period. The 2D blocking index is an extension of the one-dimensional blocking index70 to a two-dimensional map of blocking frequencies at every grid point. For each grid-point the southern gradient (GHGS) and the northern gradient (GHGN) are evaluated as follows:φ0 is the latitude of the considered grid point varying from 35°N to 75°. For each winter we calculate the ratio between the number of days when a certain grid point was blocked, i.e. the conditions GHGS > 0 and GHGN < (−10m/°.lat) are simultaneously satisfied for at least five consecutive days, and the total number of winter days (90 days). Because we have used Z500 data for 20°N–90°N, the blocking field extends from 35°N to 75°N.As a measure of local blocking frequency we have used the two-dimensional (2D) blocking indexTo identify the physical mechanism responsible for the connection between the ice cover duration and the large-scale atmospheric circulation Fig. , the 2-DSupplementary file


Analysis of photosystem II rapid light curves showed that microalgal cells in samples with high phosphate and nitrite + nitrate concentrations had reduced maximum relative electron transport rate and photosynthetic efficiency. We also observed strong couplings of PSII parameters to snow depth, ice thickness and brine salinity, which highlights a wide range of photoacclimation in Antarctic pack-ice algae. It is likely that the pack ice was in a post-bloom situation during the late sea-ice season, with low photosynthetic efficiency and a high degree of nutrient accumulation occurring in the ice. In order to predict how key biogeochemical processes are affected by future changes in sea ice cover, such as in situ photosynthesis and nutrient cycling, we need to understand how physicochemical properties of sea ice affect the microbial community. Our results support existing hypothesis about sea-ice algal photophysiology, and provide additional observations on high nutrient concentrations in sea ice that could influence the planktonic communities as the ice is retreating.Our study addresses how environmental variables, such as macronutrients concentrations, snow cover, carbonate chemistry and salinity affect the photophysiology and biomass of Antarctic sea-ice algae. We have measured vertical profiles of inorganic macronutrients  in summer sea ice and photophysiology of ice algal assemblages in the poorly studied Amundsen and Ross Seas sectors of the Southern Ocean. Brine-scaled bacterial abundance, chl  Sea ice plays an important role in Antarctic marine biogeochemical cycles, both in terms of physical, chemical and biological processes –4. Algaein situ bulk salinity profile (C-shaped) observed in young first-year ice in the Arctic [Sea ice is generally characterized as a habitat with steep gradients in temperature, salinity, radiation and nutrient concentrations . Howevere Arctic . Insteade Arctic , 16. As e Arctic , which fe Arctic , 18, 19.e Arctic –24. Due e Arctic , 26, whie Arctic . In orde2 concentrations in algal cultures [Sea-ice algae are well adapted to low-light conditions in order to grow in the shaded environment of snow and ice , 28. Howcultures –32. HoweIt has previously been suggested that the photophysiology of sea-ice algae in the Amundsen Sea is primarily controlled by radiation and nutrient availability . Snow co® bags and transported to the ship in a dark and insulated box. The sections from the physicochemical cores were vacuum-sealed and left to thaw overnight. Salinity in the melted sea-ice sections  was measured using a conductivity meter  with a resolution and accuracy of ±0.05 units. Brine salinity and volume were calculated using sea-ice temperature and bulk salinity [a fluorescence. This rapid extraction of cells resulted in a final salinity of > 28, which is recommended for minimizing the stress during physiological measurements of sea-ice algae, such as chl a fluorescence [a fluorescence was returned and pooled with the crushed core-sections after measurement. To minimize osmotic and thermal stress for the quantitative biological analyses , the ice-water mix was thawed in darkness for 12–20h together with 1 L, 0.2 μm filtered and pre-chilled seawater (approximately 1:1 ice:water ratio). Samples were processed immediately after melting.Sea-ice samples were collected from 14 sites (labeled 2–15 according to Torstensson ) in the salinity , 40. Therescence . The subv/Fm and ΔF/Fm’, respectively) were measured upon return to the ship by pulse amplitude modulation (PAM) fluorometry, using a Water-PAM equipped with blue light emitting diodes . The emitter-detector was kept cold (~0°C) during all measurements, and all samples were stored dark and cold until processed and analyzed. All samples were analyzed within 1–4 hours from collection in the field, and all sample processing was performed in a dark laboratory. Processing time was only long enough to increase the light saturation point (Ek) in two of the eleven sampled stations  was determined by applying a low level of measuring light and the maximum fluorescence (Fm) by exposing the sample to a short pulse of saturation light (> 1000 μmol photons m−2 s−1 for 0.8 s). Fm’ was determined for light-exposed cells during rapid light curves (RLCs) and non-photochemical quenching (NPQ) analysis. Variable fluorescence (Fv = Fm−F0) and maximum quantum yield of PSII (Fv/Fm) for each sample were determined in duplicated measurements for improved accuracy. RLCs were performed by measurement of ΔF/Fm’ ((Fm’−F0) / Fm’) of quasi-adapted (15 s) cells at nine levels of actinic light  in the emitter-detector unit. Relative electron transport rate (rETR) was calculated by ΔF/Fm’ multiplied by PAR intensity. Photosynthetic parameters  were calculated according to Jassby and Platt [−2 s−1 for 270 s, and calculated by (Fm−Fm’)/Fm’. Incubation time was regularly verified to be saturating for quenching parameters by light-inductive curves. Due to time constraints, NPQ was not measured at every station.The maximum and effective quantum yield of photosystem II  and sonicated using a Vibra-cell sonicating probe, operating at 80% in 5-s pulses. High performance liquid chromatographic (HPLC) analyses of the extracts were performed , using ad Garner .−5) for 10 min in darkness. Cell counting was performed with a FACScalibur flow cytometer , using side scattering light (SSC) and green fluorescence (FL1) for detection. Flow rate was determined with an internal standard of 1 μm FluoSpheres . The concentration of FluoSpheres was quantified by triplicated measurement together with BD Trucount absolute counting beads . Bacterial abundances were either integrated over area, or corrected to brine volume according to Frankenstein and Garner [Melted sea-ice samples were fixed in 1% glutaraldehyde  and stored at −80°C until analysis. Bacteria were stained with SYBR Green Nucleic Acid Gel Stain  of melted sea ice was determined by potentiometric titration of 40 mL sample in open cell with 0.05 mol l−1 hydrochloric acid using a Titrino system  [μmol kg−1, obtained by triplicate analysis of one sample on a daily basis. The accuracy was checked against a certified reference material (CRM) supplied by Andrew Dickson  measured at the beginning and at the end of 20 samples.Total alkalinity (Azerland) . The prepH was determined spectrophotometrically, using m-cresol purple and a diode-array spectrophotometer, HP8452 . The anaT), salinity and temperature, using the carbonate speciation program CO2SYS 2.1 [1 and K2) of Mehrbach [4 determined by Dickson [T and DIC (derived from AT and pH) were used to recalculate the carbonate system in the brine.Total dissolved inorganic carbon (DIC) was calculated based on measured data of pH and total alkalinity . Samples were analyzed at the Sven Lovén Center for Marine Infrastructure, Kristineberg, Sweden, using colorimetric methods . For comRedundancy analysis (RDA) was performed in CANOCO 5 to explore linkages between biological and environmental variables. RDA can effectively visualize potential linear relationships of multivariate data matrices by producing an ordination plot constrained to present a combination of multiple predictor variables responsible for the majority of the total variation in a dataset. Combinations of highly correlated environmental data were excluded from the analysis, such as temperature and salinity. Bootstrapping was performed using Monte Carlo Permutation Procedure (MCPP) tests, executed with 1000 iterations.Multiple and simple linear regressions were performed in R 3.1.1 , and useAll sea-ice samples in this study came from first-year pack ice (sometimes rafted ice), except for station number 15 (McMurdo Sound) where land fast ice was sampled. The sea ice in McMurdo Sound had a typical salinity and temperature profile of land fast ice, and differed significantly from the pack ice in the Amundsen Sea. Average ±SD sea-ice thickness during the entire study was 1.19 ±0.41 m, with a snow cover varying between 0–0.55 m . The tema and bacterial abundances (excluding surface slush layer) were 4.3 ±6.1 mg m−2 and 6.5×1011 ±4.7×1011 cells m−2, respectively  of the total variance in DIC. There was no significant correlation between DIC and bacterial abundance  in 17 samples from middle sections of the sea ice column , where bacterial abundance explained 38.9% and 12.8% of the variability, respectively. Fucoxanthin concentration was positively correlated with silicic acid concentration (p = 0.0003), but only explained 6.1% of the variability.Brine-scaled Chl max, Ek, and αPSII) were snow depth, brine salinity and DIC concentration  and the main explanatory variables . Model outputs are summarized in v/Fm  and accounted for 25.7% of the variability in Fv/Fm  was negatively correlated with brine salinity , whereas the maxima in bacterial abundance were also often associated with the middle sections of the sea ice column. Chl a was increasing with depth in the sea ice column, which could partly be explained by low-light induced production of photosynthetic pigments, which has previously been described as a decrease of the ratio between particulate organic carbon and chl a as a response to snow accumulation [a concentration reached relatively high levels (maximum 421 μg l−1), depth-integrated chl a concentrations in Southern Ocean sea ice have recently been estimated to be higher than in our study [a concentrations are more comparable to spring and autumn concentrations, rather than summer values [The sea ice in this study was sampled in an advanced melting stage. While the sea ice lacked the typical C-shaped salinity profile as in young and cold ice , the chlmulation . Althougur study , 33. We ur study , 33. Henr values . This coa in sea ice is often accompanied by low nutrient concentrations, low DIC concentration, accumulation of dissolved organic matter, increased ammonia concentration, high bacterial abundance and increased rate of viral infections [a were also accompanied by high bacterial abundances, but neither pH nor DIC concentration correlated well with either chl a or bacterial concentrations. Also, unlike the studies cited above, chl a was positively correlated with macronutrient levels. The low degree of correlation between chl a and DIC suggests that these variables may not be good indicators for net DIC uptake or production during the time of sampling. However, DIC is also affected by other processes such as CO2 exchange and calcium carbonate dissolution or precipitation, which may have counteracted the DIC change due to primary production [a concentration and rETRmax. This post-bloom situation is further supported by the high occurrence of potentially heterotrophic dinoflagellates in the sea ice identified in a concurrent study [High concentration of chl fections , 54–56. oduction . As the oduction . Therefont study , that arnt study , 58.a maximum was generally located at the bottom of the ice, although it is not uncommon that high amounts of chl a is found in the middle sections of flooded pack ice [The bulk concentrations of macronutrients were all in similar ranges as previously reported for Antarctic summer pack ice . Concentpack ice . There wpack ice . Howeverpack ice . This maa concentration and bacterial abundances. This may possibly be due to high rates of remineralization in this relatively warm summer sea ice [max was reduced at high concentrations of phosphate and nitrite + nitrate, suggesting that the algae may experience stress and not being capable of maintaining their maximal potential photosynthetic rates.It has previously been discussed that nutrient concentrations are the main controlling factor for ice algal biomass distribution in the Amundsen Sea in the late summer through surface flooding . However sea ice . Interesa was also positively correlated with inorganic macronutrient concentration, but did not correlate well with DIC concentration. In combination with high macronutrient concentrations in the brine, and little influence of high chl a concentration and bacterial abundance on the carbonate system, we believe that inorganic macronutrients are unlikely to have limited microalgal cellular physiology in this study. On the contrary, macronutrients  were accumulated to high concentrations in the samples with high algal and bacterial biomass, suggesting an imbalance between production and consumption of nutrients. It is possible that a stressed and decaying standing stock of algae release large amounts of internal pools of compounds, a process to which the contribution of macronutrients levels in sea ice is still unknown. The release of nutrients from sea-ice algae during the melting process of sea-ice cores has previously been discussed in detail [Chl n detail , 61. Dirn detail . Howevern detail . Howevern detail . Considen detail , it is pn detail , but we a concentrations predict phosphate and nitrite + nitrate levels well, but not silicic acid. Fucoxanthin concentration correlated well with chl a and did not provide a better fit of silicic acid over chl a concentration (6.1 vs. 5.6% of the variability), suggesting that diatoms may indeed have been the main primary producers in the samples.Accumulation of phosphate and ammonium are common throughout the season in Antarctic pack ice, and can reach substantial values in the summer, probably due to the adsorption to organic particles –a procesSea-ice micronutrient dynamics is still an under-studied field, but believed to play an important role in Southern Ocean nutrient cycling near the marginal ice zone . Very lia concentration, and were found in abundances anticipated for Antarctic summer sea ice [In agreement with other studies , 65, bac sea ice . Strong  sea ice . However sea ice , and it  sea ice . Reducti sea ice , which ck was strongly adjusted to the first ~0.2 m of snow loading, and subsequently leveled-out, following the exponential attenuation of PAR through matter. This observation supports the concept of a broad range of photoacclimation and plasticity in pack-ice algal communities [v/Fm and αPSII increased with sampling depth, highlighting the importance of efficient photoacclimation strategies at varying light intensities in sea ice. Plastic responses to radiation may be especially important for sea-ice algae in melting summer ice conditions in order to adjust their PSII performance to optimize energy demand at varying PAR levels. Plasticity may also be an important adaptation for the sea-ice community that is dispersed into the water column, as the ice is melting and thereby seeding the pelagic bloom [Pack-ice algal communities show a plastic response in PSII kinetics to elevated radiation, and can withstand relatively high irradiances . As Soutmunities , and sugic bloom .max and αPSII, differentiating the effects of brine salinity and snow depth becomes challenging. Although the temperature gradient is less pronounced in surface-flooded summer pack ice, as compared to cold and growing sea ice [max and αPSII, and increased NPQ. Interestingly, rETRmax and αPSII were highest at the lowermost salinities, suggesting that this sea-ice algal community could be adapted to a lower salinity than experienced in the water column of the Southern Ocean [v/Fm by 6–9% when temperature was increased by 4°C [Due to correlation between predictors in the multiple regressions models for rETR sea ice , the micrn Ocean . We belid by 4°C , 71. TheA previous experimental study on algal assemblages from land fast sea ice suggests that decreases in salinity are more stressful than increases in terms of PSII performance . This isAs the areal extent and thickness of sea ice in the Amundsen Sea has diminished during the last 35 years , the phya and phosphate and nitrite + nitrate, suggesting that the autotrophic community was in a decaying state during sampling, where microbial remineralization exceeded algal uptake. Although macronutrient concentrations did not seem to be limiting photosynthetic rates in the brine channels of surface-flooded pack ice in our study, we speculate that sea ice in advanced melt stage may lack certain micronutrients to sustain primary production in sea ice similar as to the Southern Ocean overall.As the sea-ice situation in polar oceans is currently undergoing rapid changes, it is important to understand how physicochemical properties and nutrient distribution affect key ecosystems and biogeochemical processes. There is also relatively little physiological and biogeochemical data from pack ice in the Amundsen Sea available, which is a key area for studying diminishing sea-ice situation in the Southern Ocean. Although few studies that focus on sea-ice microalgal photophysiology are as extensive  as the present study, results from this work are fairly consistent with previous findings , 33, 75.S1 FigThe numbers 4–15 represent station number during the OSO10/11 cruise in the Amundsen and Ross Seas.(EPS)Click here for additional data file.S2 FigIB Oden.Data were collected using a 2π PAR sensor placed on top of the bridge of (EPS)Click here for additional data file.S3 Figa) represents 95% prediction intervals of the fitted line. All concentrations are scaled to brine volume.The grey area in ((EPS)Click here for additional data file.


Precision medicine (PM) is changing the scope of allergy diagnosis and treatment. An in vitro IgE assay, a prototype PM method, was developed in the sixties and has garnered increasing interest because of the introduction of recombinant components in the test. More recently, microarrays of allergen components have significantly improved the ability to describe the IgE profile. Aim of this study was to evaluate the characteristics of the newly developed Allergy Explorer (ALEX), a macroarray containing both extracted “whole” allergens and molecular components. This method allows the acquisition of an IgE profile comprising 282 reagents , resulting in the widest screening of potential allergens available.Sera from 43 patients with allergies were assayed with ALEX and then with ImmunoCAP ISAC. The results of the two tests were compared, and the consistency of the molecular results with the presence of IgE in the relevant extract was also evaluated.A good correlation between ISAC and ALEX was observed. The ALEX results for second-level tests  were consistent with the results obtained for the relevant components.Despite differences in the methodology, the IgE profiles detected for molecular allergens by ALEX and ISAC were very similar. The differences were mainly related to the lower dynamic range of ALEX and to the use of a CCD inhibitor in the first incubation phase, which reduced the binding of IgE to CCD, as represented in the extracted allergens and components.Based on our findings, ALEX is a novel tool for describing the IgE profile in a PM setting, where the IgE assay must be performed on many allergens and components. In particular, polysensitized patients and patients with pollen-food syndrome will have a real advantage due the combination of the second and third levels of allergy diagnostics in the same chip. Precision medicine (PM) has a relevant impact on many human sciences and a special impact on the diagnosis and treatment of allergic diseases . Indeed,A/mL. Total IgE is also measured. Finally, an arbitrary calibration curve is obtained by reacting four spots with decreasing concentrations of specific IgE corresponding to < 0.3 kUA/L, 0.3 - 1 kUA/L, 1 - 5 kUA/L, 5 - 15 kUA/L and > 15 kUA/mL.ALEX was developed by MacroArrayDX . This array contains 282 reagents . The large majority of inhalant, food, latex and Hymenoptera allergen families are represented  were different when assayed with ALEX and when assayed with other methods (such as specific IgE for extracts or components). Starting from this prestudy evidence, with a confidence level of 95% and a standard error of 0.05, the calculated sample size resulted in 43 different sera. Due to the large amount of allergen families  and the virtual impossibility of studying all the possible families in a single work, sera with certain characteristics were selected. Therefore, samples from patients with a known reactivity to grasses (where the largest number of molecular components was available) and cross-reacting components, particularly PR-10, profilins and LTPs, were used . In thisStatistical analysis was performed by using the statistical routines of Microsoft Excel and PAST v3.16, a free software for scientific analysis.Aspergillus fumigatus, birch, dog, hazel, Dermatophagoides pteronyssinus, D. farinae, cat, codfish, hen egg, apple, wall pellitory, timothy grass, peach, and ash  and represented in a suitable number in the cohort of patients evaluated, and second, a comparison of the capacity of identifying the same component families. The results of the single-component comparisons are shown Fig. . It is eomponent . A similRegarding the capacity of ALEX to identify component families, compared to the capacity of ISAC, a statistical analysis was performed, and the results are shown in Table r > 0.39, p > 0.01) was observed in 10 out of 12 patients. In a single patient (identified by K), the correlation coefficient R was 0.38 (p < 0.02), and in only a single patient (L) could any correlation be observed. However, in these patients, the scores were extremely low and below any clinical or laboratory significance.Another comparison was made by plotting the results of components present in both ALEX and ISAC in the same patient. Figure Finally, the effect of the CCD inhibitor was evaluated in some representative samples. Figure In the absence of a gold standard for the evaluation of the performance of an assay of specific IgE, any correlation between different methods should be carefully evaluated. Indeed, the SPT cannot be used to evaluate the results of any serological assay, as it may be positive even in the absence of specific IgE. Specific IgE (assayed on the whole extract) cannot be directly compared with specific IgE measured from the molecular components: indeed, the positivity to the whole extract only rarely corresponds to the positivity of all the relevant components available . FinallyHaving in mind these concepts, in the present study, we analyzed the capacity of ALEX, a novel tool that could be properly used in the bottom-up strategy of allergy diagnostics, to detect sensitization to allergens and components.To validate ALEX performances, it was considered that this assay was developed on nitrocellulose as an immunosorbent, and the ligation of the allergen to the solid phase was performed by a nanoparticle. Therefore, within the same assay, a comparison of results from the whole extract and the results from relevant allergen-specific components could be accurately performed. A significant correlation between the results of whole extracts with those of the relevant components was observed. This finding is particularly interesting because, in the past, this strict correlation was not completely observed . Some poWhen molecular components on ALEX were compared with the same components on ISAC, it was considered that the solid phases were different, the serum dilutions were different, the second antibody was probably different, and the enzyme substrate was also different. Additionally, ALEX uses a CCD inhibitor while ISAC does not. Nevertheless, laboratory methods are “artificial” procedures that attempt to mimic in vitro what is suspected to occur in vivo and, more importantly, the results from in vitro tests are used to support the allergist’s diagnosis and therapy. However, despite technical differences, a significant correlation between methods should be achieved. At the component level, the correlation between the results of ALEX and those of ISAC was more than positive, at least for the IgE profiles used in the present preliminary study. Indeed, we focused on samples characterized by a strong IgE reaction against pollens and related cross-reacting allergens because this is an area in which molecular diagnostics seems to offer the most useful results . All theThe capacity to detect sensitization to component families was characterized by a certain heterogeneity. Possible explanations are that at the component level, different molecules were used in the two methods, resulting in a different capacity of sera to recognize different epitopes. In addition, the use of a CCD-inhibitor in ALEX may generate further differences. Finally, the strict correlation between the results of molecular components at a single patient level is the final evidence that ALEX performs similarly to ISAC.The role of the CCD inhibitor is interesting . Allergi. The combination of second- and third-level assays in the same test allows us to define, in a single hit, the presence of IgE sensitization and whether the reaction is genuine or cross-reactive. Considering the overall social and personal costs, the availability of all the results in a single analytical session has unequivocal advantages. This seems particularly interesting considering that the raw cost of a single allergen or component on the ALEX chip is approximately 0.30 €. Despite the fact that this may be disturbing for some allergists [One of the principal added values of ALEX is its capacity to provide results on whole extracts and relevant components within the same assaylergists , the advIn conclusion, ALEX, the immunoassay for specific IgE to whole allergens and relevant molecular components, is an interesting new approach to the bottom-up  diagnosi


We used functional magnetic resonance imaging to examine whether motivational-salient cues could exert a differential impact on proactive (the restrain of actions in preparation for stopping) and reactive (outright stopping) inhibition. Fourteen high-frequency poker players, and 14 matched non-gambler controls, performed a modified version of the stop-signal paradigm, which required participants to inhibit categorization of poker or neutral pictures. The probability that a stop-signal occurs  was manipulated across blocks of trials, as indicated by the color of the computer screen. Behavioral analyses revealed that poker players were faster than controls in categorizing pictures across all levels of proactive motor response inhibition . Brain imaging analyses highlighted higher dorsal anterior cingulate cortex activation in poker players, as compared to controls, during reactive inhibition. These findings suggest that, due to their faster rates of stimulus discrimination, poker players might have recruited more cognitive resources than controls when required to stop their response (reactive inhibition). Nevertheless, no main effect of stimulus type was found, on either proactive or reactive inhibition. Additional studies are, therefore, needed in order to confirm that investigating the dynamics between reactive and proactive inhibition offers a discriminative analysis of inhibitory control toward motivational-salient cues. A main consequence of this increased exposure is that it could foster temptation to gamble in frequent gamblers4.Gambling has never been so easily accessible and readily available. It is possible to bet everywhere, at every moment, and simultaneously using different platforms. The high volume of gambling advertising is also there to remind you to do so. As a matter of fact, gambling cues are present in newspapers, TV, radio, sports arenas, and the Internet8), reward anticipation , and affective decision-making . Interestingly, gambling cue reactivity was also associated with anterior cingulate cortex (ACC) and dorsolateral prefrontal cortex (DLPFC) activations6. Brain activations within these areas overlap with some of the neural pathways underlining motor response inhibition, namely the ACC and the DLPFC, which are often involved in the anticipation/preparation of response conflicts, and in selecting superordinate sets of action-selection rules11. It follows that enhanced resources engaged in the processing of salient stimulus should leave fewer resources available for effortful control14. Hence, one may advance the notion that motivational salience directed at gambling cues could lower gamblers’ ability to inhibit a motor response toward those stimuli.Congruent with this view, functional magnetic resonance imaging (fMRI) studies highlighted that problem gamblers exhibit increased activation in salience/motivational brain circuitry while viewing gambling pictures refs . Neural 15 have examined the interaction between stimulus saliency and motor response inhibition in gamblers. Consistent with previous work on cue reactivity, this fMRI study highlighted the idea that gambling-related stimuli are flagged as more salient by individuals with problem gambling. This was reflected by higher DLPFC, ACC and ventral striatal activations, as compared to non-gambler controls. Surprisingly, problem gamblers were also better than controls at inhibiting their motor response toward gambling cues, and showed lower activation of the DLPFC and ACC regions. One explanation for this result is that this sample of gamblers was recruited from addiction treatment centers, where they received cognitive behavioral therapy. This could have lowered their motivational-approach tendencies towards gambling cues, i.e., stimuli that are related to their abstinence/moderation goals19. Accordingly, enhanced response inhibition toward food cues has been evidenced in overweight adults who are high on dietary restrain22. By contrast, research has shown that motivationally salient stimuli  could hamper motor response inhibition in both frequent and (non-restricting) problem users24. Besides, in van Holst et al.15, the type of stimuli was not adapted to gamblers’ preferred type of gambling (e.g. poker vs. blackjack). This could have further decreased the motivational-salience attached to gambling cues, and its subsequent  impact on motor response inhibition. For instance, Pessoa and colleagues25 showed that low-emotional stimuli increased motor response inhibition, and the opposite was found for high-emotional cues. Thus, motor response inhibition should be decreased in (non-restricting) frequent gamblers who are required to inhibit gambling cues that correspond to their daily-life gambling habits.Currently, only van Holst and colleaguesproactive and reactive motor response inhibition, which refer to distinct temporal dynamic modes of motor response inhibition28. Proactive inhibition can be conceptualized as a form of “early selection” in which goal-relevant information is actively maintained to optimally bias attention, perception and action systems in a goal-driven manner, and is used to restrain actions in preparation for stopping . Reactive inhibition is a “late correction” process, which is triggered by external signals (e.g. to brake when a pedestrian suddenly cross the street), and results in the stopping of the ongoing action. Put differently, under reactive control, goal representations are only activated at the time in which they are needed28. Proactive control, by contrast, relies upon the anticipation and prevention of the stop signal before it occurs28. At a neural level, it has been demonstrated that proactive and reactive inhibition activate common brain areas, including the superior, middle, and inferior frontal gyrus, supplementary motor area, angular gyrus, and the striatum, in both right and left hemispheres40. This shared neural pathway suggests that proactive and reactive inhibition might rely on a common network involved in “braking” motor output when it is weakly activated (proactive inhibition), and in “stopping” motor output completely when strongly activated (reactive inhibition)36. Proactive and reactive inhibition might also activate specific neural pathways, with reactive inhibition associated with right DLPFC, right VLPFC and anterior supplementary motor area activations, which could reflect stimulus-driven attention, and action reprogramming from going to stopping43. Proactive motor control has been reported to specifically activate the right and left superior parietal lobule, which could reflect top-down influence over motor control39.Another gap of knowledge from the literature is whether salient-motivational cues interfere with both 38. Zandbelt and colleagues38 showed that, in comparison to control subjects, proactive inhibition was reduced in schizophrenia patients, while reactive inhibition did not differ between the two groups. More specifically, as compared to controls, patients failed to slow down responding as the probability that they may have to stop increased . At a brain imaging level, this pattern was associated with a failure to activate the right striatum, the right inferior frontal cortex, and the left and right temporoparietal junction. In another study, van Rooij and collaborators33 highlighted that war veterans with posttraumatic stress disorder (PTSD) showed reduced reactive inhibition , as compared to non-military controls, along with a decreased inhibition of the left pre/postcentral gyrus. The veterans with PTSD also exhibited impaired behavioral proactive inhibition. Furthermore, the PTSD group showed a reduced right inferior frontal gyrus response during proactive inhibition, as compared to a group of veterans without PTSD. Taken together, these findings confirm that investigating both reactive and proactive inhibition might offer a more nuanced, discriminative and fine-grained analysis of inhibitory control.The importance of examining both proactive and reactive components of motor response inhibition has been further emphasized by recent fMRI studies undertaken in sub-clinical and clinical sampleset al.15) to inhibit cues that matched their preferred gambling games (poker pictures). At a behavioral level, we predicted that, when compared to a group of non-gambler controls (n = 16), poker players would exhibit lower proactive and reactive inhibition while categorizing poker cues. Second, we expected that poker players would exhibit lower brain activation than controls during proactive and reactive inhibition. Third, in line with previous neuroimaging studies on gambling cue reactivity15, we also hypothesized that poker players, as compared to controls, would show enhanced brain activity during the viewing of poker pictures, especially in the salience/motivational brain circuitry .The goal of this study was to examine, at both behavioral and neural levels, the impact of gambling cues on proactive and reactive motor response inhibition in high-frequent gamblers. Based on the aforementioned argumentation, we recruited one specific “type” of gamblers . Those pretests aimed to test whether categorization RT is modulated by the level of stop-signal probability (green < yellow < orange < red). In addition, we expected that (i) mean p[respond|signal])  will approximate 0.50, which would confirm the effectiveness of the tracking procedure; and (ii) mean failed stop-signal RT should be faster than mean go signal RT , which would be used as a criterion of independence between the finish times of the go and the stop responses .The SST was first pretested in a sample of students  = 100.51, p < 0.0001, η2 = 0.87; see also Figure p[respond|signal]) was close to 0.50 for both the neutral  and the poker  stimuli; and that the mean failed stop-signal RT  was lower than the mean go_signal RT  = 14.91, p = 0.002, η2 = 0.50). In addition, we observed that SSRT values were similar to those observed in previous studies using a SST  increased as a function of the level of stop-signal probability  = 161.38, p < 0.001, η2 = 0.86  and stimuli categorization accuracy; Table p < 0.001). We observed a main effect of group, F = 4.30, p = 0.048, η2 = 0.14, indicating that poker players were faster in categorizing neutral and poker cues across all levels of stop-signal probability . We observed no main effect of stimulus type and no significant interaction .Analyses revealed that categorization RT (in milliseconds) increased as a function of the level of stop-signal probability, p[respond|signal]) was close to 0.50 for both the neutral  and the poker  stimuli, which confirm the effectiveness of the tracking procedure for both types of stimuli. We also observed that mean failed stop-signal RT was faster than mean go_signal RT, F = 17.93, p < 0.0001, η2 = 0.43, which is a criterion for the independence between the finish times of the go and the stop responses , and p[respond|signal]). Repeated-measures ANOVA revealed that gamblers  did not differ form controls  = 0.69, p = 0.41, η2 = 0.03. There was also no main effect of stimulus type or group, and no significant interaction effect .First, we observed that the overall sample mean of N = 28). These contrasts reveal activations in a widespread network featuring frontal, paracingulate, insular, striatal, temporal, parietal, and occipital regions. However, no significant between-groups difference was observed on whole brain activation for the effect of stop-signal probability.Figure N = 28). Together, poker players and control subjects activated a network encompassing frontal, paracingulate, striatal, parietal and occipital regions. Between-groups analyses revealed that, when inhibiting successfully their motor response toward poker cues, poker players showed more activation than controls in the dorsal anterior cingulate cortex , were ran on these two contrasts. For the successful stop contrast, we observed that poker players exhibited higher brain activation than controls, including cluster of activation encompassing the dACC . We then ran Spearman Rho correlation analyses  between parameter estimates and behavioral index of proactive and reactive inhibition. For proactive inhibition, we used the stop-signal probability slope38, defined as the change in go-signal response time per stop-signal probability unit increase. For reactive inhibition, we used (i) SSRT values, and (ii) the probability of responding on stop-signal, p(responding), averaged across all stop-signal probability contexts . These analyses revealed a significant negative correlation between dACC parameter estimates, and the stop-signal probability slope, rho(28) = −0.47, p = 0.03. Thus, the lower the proactive adjustment is , the higher the dACC activity during the subsequent successful reactive inhibition. No significant correlation was observed between dACC parameter estimates with either SSRT, rho(28) = 0.11, p = 0.62, or p(responding), rho(28) = 0.36, p = 0.14. Noteworthy, there was also no correlation between SSRT and p(responding), rho(28) = 0.30, p = 0.15, which might be due to the fact that the SSRT  exhibited higher activation within the pre- and post-central gyrus. During successful reactive inhibition poker players and controls exhibited higher activation within the occipital pole. During unsuccessful reactive inhibition, participants (N = 28) exhibited higher activation within the pre- and post-central gyrus and the occipital pole. These activations are detailed in Tables During proactive inhibition, participants  and reactive (a “late correction” process that results in the stopping of the ongoing action) motor response inhibition in a sample of highly frequent poker players and matched non-gambler controls. We used a modified version of the stop-signal paradigm that requested participants to inhibit categorizing poker and neutral pictures, and in which the probability that a stop-signal occurs was manipulated according to the color of the computer back screen.47. They also exhibit attentional bias toward gambling pictures at both early  and reactive  motor response inhibition. However, poker players were faster than controls in categorizing poker and neutral cues during “go” trials . This result is congruent with previous research, which showed that frequent gamblers (ranging from non-problem to high problem gambling) are faster in detecting gambling-related cues during rapid serial visual presentation tasks40. This includes frontal, insular, striatal, temporal, parietal, and occipital regions. In addition, both proactive and reactive inhibition activated the superior, middle, inferior, orbital frontal gyri, cingulate gyrus, superior parietal lobule, putamen and caudate. This neural pathway was activated in both the right and left hemispheres. These findings further confirm those from previous neuroimaging studies on proactive and reactive inhibition in showing that these two modes of response control share a common brain network36. This common neural network might be involved in “braking” motor output when it is weakly activated (proactive inhibition), and in “stopping” motor output completely when strongly activated (reactive inhibition)36. Importantly, between-group analyses showed that poker players exhibited higher brain activation than controls during reactive inhibition . This pattern of activation was revealed within the dACC. This region plays a key role in cognitive control by monitoring the occurrence of response conflict58, such as when simultaneous incompatible response tendencies are triggered during reactive inhibition on the stop-signal task . In other words, the lower the proactive adjustment is , the higher the cognitive resources needed during subsequent reactive inhibition.At a brain imaging level, within-group analyses revealed that contrasts for proactive and reactive motor response inhibition activated a widespread network that is very similar to that reported by previous brain imaging studies62, and that poker gamblers might rely on more effortful-reactive inhibitory control, they should be less able to undertake repeated and extended inhibitory effort during poker cues exposure. This “backfiring” pattern could relate to a mechanism of ego depletion, which has been reported to occur when an extended inhibitory effort in one domain causes subsequent inhibitory impairment in a second domain63. For instance, Muraven and colleagues64 found that an episode of affective inhibition resulted in a subsequent reduction in the ability to exercise motor control, and that prolonged cognitive inhibition resulted in a deficit in inhibiting emotional stimuli.One major implication of this finding is that, because reactive motor response inhibition is a high-demanding process66 and social drinkers67, and could lead the individual to respond more forcefully to salient stimuli68. At a brain-imaging level, it has been shown that stimulus availability and expectancy increases neural cue reactivity , as well as cognitive control . Thus, one option to expose the effect of stimulus type on (proactive and reactive) motor response inhibition would be to manipulate perceived availability attached to the action of poker . Alternatively, future studies should focus on the impact of addiction-related cues in quitting-motivated addicts. Indeed, it has been shown that response inhibition toward food cues is enhanced in overweight adults who are attempting dietary restrain72. Similar findings have been reported in treatment-seeking addicted individuals, who exhibited intact73, or enhanced15 motor response inhibition towards drug or gambling addition related-cues, when compared to non-addicted controls. This can be accounted for, if one assumed that abstaining or restraining gamblers, in contrast to the current frequent gamblers, develop an active avoidance strategy toward cues to support their abstinence/moderation goals69. Another important point is that our modified version of the stop-signal task involved explicit manipulation of stop-signal probability . Hence, despite the validation indices that were obtained for reactive inhibition  close to 0.50; mean failed stop-signal RT faster than mean go_signal RT; mean SSRT values similar than in studies using a standard stop-signal task) and proactive inhibition , the complexity of the present design might have decreased the influence of motivational cues on response inhibition. In addition, the use of a high value for the initial SSD  might have “forced” participants to wait for stop-signal . This might have influenced the optimal assessment of motor response inhibition in the current stop-signal task, which is a paradigm that requires participants to respond fast, and not to wait for stop-signals. Hence, future studies should examine proactive and reactive inhibition using shortened initial SSD value and/or assess whether these two components of inhibition are significantly modulated  when different initial SSD values are used.Contrary to our hypotheses, we observed no significant impact on the type of stimuli during either proactive or reactive motor response inhibition. Specifically, at a behavioral level, poker cues did not impact poker players proactive RT slowing and SSRT. At a neural level, cue reactivity contrast revealed that poker stimuli activated mainly the primary motor cortex, i.e., the brain network involved in overt motor action during go trials . One explanation for this negative finding is that the action of poker gambling was not perceived as “available” or “expected” by poker gamblers throughout the experiment. In other words, in the current study, the stop-signal task was not followed by the action of poker playing. Hence, the viewing of poker pictures might not have triggered strong motivational-approach in poker players because the stimulus “complex” was not complete. Consistent with this account, perceived availability has been shown to increase craving in smokerset al. study15, i.e., another neuroimaging study that examined the impact of gambling cues on motor response inhibition in gamblers. Furthermore, our sample was selected using stringent selection criteria, resulting in a homogeneous cohort of gamblers in terms of gambling game preferences .Finally, because the sample sizes of our groups were modest, non-significant behavioral and neuroimaging results must be interpreted with caution. Nevertheless, our final sample is comparable to that in van Holst In summary, the present findings indicate that, compared to non-gambler controls, highly frequent poker players show more activation of the dorsal anterior cingulate cortex during reactive response inhibition of neutral and poker pictures. This pattern might be due to poker players’ faster rates of stimulus discrimination exhibited across varying levels of proactive motor response inhibition. The present results confirm that investigating both reactive and proactive inhibition might offer a discriminative and fine-grained analysis of inhibitory control, and that fMRI is a good approach for studying the dynamics underlining these two processes. To a broader extent, these findings suggest that humans need to trigger additional cognitive resources, when required to stop their motor response, while being embedded in an environment featuring salient-motivational stimuli. Examining the dynamics between proactive and reactive control could, therefore, advance our knowledge of humans’ ability to control hedonic habits, and further inform the development of novel intervention strategies aimed at strengthening self-control.Seventeen frequent poker gamblers  and 16 non-gambler controls participated in this study . All participants gave written informed consent to the experimental procedure, which was approved by the University of Southern California Institutional Review Board and this study was performed strictly in accordance with the approved guidelines.Poker players were recruited on the Internet through advertisements displayed on online forums for poker players based in Los Angeles. The ads asked for participants who “played poker frequently in casino” to participate in a one-day study to explore factors associated with attentional processing in poker gambling. Controls were recruited by word of mouth from the community. For both gamblers and controls, a screening interview was conducted (online or through the phone) in order to examine gambling frequency, problem gambling severity, history of therapeutic intervention focused on gambling behavior, substance use , and medical history (included in the MRI screening form). Problem Gambling severity was assessed with the South Oaks Gambling Screen (SOGS). Current sample of gamblers ranged from non-problem to high-problem gambling. Poker players’ SOGS scores and information on their frequency of poker playing (per week) is depicted in Supplementary Materials, Table 74. In this task, participants had to discriminate, as fast as they can, between neutral and poker-related pictures. Subjects were asked to stop their response when they heard a tone . During the experiment, stop-signal delay  was continuously adjusted , separately for neutral and gambling cues , according to a tracking procedure to obtain a probability of stopping of 0.5060 if stopping was successful, then stopping was made more difficult on the next stop-trial by increasing SSD by 25 ms. The process was reversed when stopping failed.Participants performed a modified stop-signal task , 17% (yellow), 25% (orange), and 33% (red). Trials were divided into blocks of 9, 18 or 27 trials in a same context. Block length was randomized with the restriction that there were no context repetitions  and that blocks of 9, 18 and 27 trials occurred with equal probability.n_neutral = 64, n_poker = 64; 17%, n_neutral = 45, n_poker = 45; 25%, n_neutral = 40, n_poker = 40; 33%, n_neutral = 36, n_poker = 36) and 82 stop-signal trials  were presented in a single run in pseudorandom order. Poker pictures were taken from casino scenes and were matched on visual complexity with the neutral pictures  on an IBM compatible PC. Participants’ responses were collected online using an MRI-compatible button box.Before entering the MRI scanner, participants were first trained on the SST in order to familiarize them with the task. One experimenter remained alongside the participants during the training in order to ensure that the task was properly understood. The training consisted of 9 trials for each of the four background color contexts . During the MRI scanning session, participants lay supine on the scanner bed, and viewed visual stimuli back-projected onto a screen through a mirror attached onto the head coil. Foam pads were used to minimize head motion. Stimulus presentation and timing of all stimuli and response events were achieved using Matlab 7.14  and Psychtoolbox 3.0.12 .fMRI imaging was conducted in a 3 T Siemens MAGNETOM Prisma scanner in the Dana and David Dornsife Cognitive Neuroscience Imaging Center at the University of Southern California. Functional scanning used a z-shim gradient echo EPI sequence with PACE (prospective acquisition correction). This specific sequence is dedicated to reduce signal loss in the prefrontal and orbitofrontal areas. The PACE option can help reduce the impact of head motion during data acquisition. The parameters are: TR = 2000 ms; TE = 25 ms; flip angle = 90°; 64 × 64 matrix size with resolution 3 × 3 mmwww.fmrib.ox.ac.uk/fsl). The first three volumes, before performance of the task, were automatically discarded by the scanner to allow for T1 equilibrium. The remaining images were then realigned to compensate for small residual head movements that were not captured by the PACE sequence75. Translational movement parameters never exceeded 1 voxel in any direction for any subject or session. Data were spatially smoothed using a 5-mm full-width-half-maximum (FWHM) Gaussian kernel. The data were filtered in the temporal domain using a non-linear high pass filter with a 100-s cut-off. A three-step registration procedure was used whereby EPI images were first registered to the matched-bandwidth high-resolution scan, then to the MPRAGE structural image, and finally into standard (MNI) space, using affine transformations75. Registration from MPRAGE structural image to standard space was further refined using FNIRT nonlinear registration77. Statistical analyses were performed in the native image space, with the statistical maps normalized to the standard space prior to higher-level analysis.Image preprocessing was carried out using FEAT  version 6.00, part of the FSL package , which is a measure of the latency of the inhibition process. The SSRT was estimated through the integration method46 and pooled across stop-signal probability levels39. The integration method involves to subtract the mean SSD from nth RT  multiplied by the overall p [respond|signal]). The SSRT was estimated separately for neutral and gambling pictures. Go trials with response times of more than 1.5 times the interquartile range away from the 25th and 75th percentiles of the response time distribution of each stop-signal probability level were defined as outliers.Behavioral data were analyzed using custom written software in Matlab 7.14  and SPSS 24 . Response times  and accuracy were calculated for each stop-signal probability level separately. In keeping with previous studiesDue to poor task performance, data from three gamblers and one control were excluded. These participants exhibited more than 70% of go response during stop-signal trials . Another control participant was excluded due to a technical issue  yielding 14 gamblers and 14 controls for behavioral and fMRI analyses. Statistical analysis of proactive inhibition consisted of a repeated-measures analysis of variance (ANOVA) on mean go-signal response times in each stop-signal probability context , stimulus type , and group (control vs. poker players) as factors. Statistical analysis of reactive inhibition involved repeated-measures ANOVA on SSRT, with stimulus type , and group (control vs. poker players) as factors.The brain imaging data were modeled at the first level using a general linear model within FSL’s FILM module using FEAT. First-level statistical analysis included the following conditions as regressors: successful stop-signal trials, unsuccessful stop-signal trials, go-signal trials stop-signal probability levels , for both poker and neutral pictures . The event onsets were convolved with canonical hemodynamic response function  to generate regressors used in the GLM. Temporal derivatives and missed go responses for go-signal trials were included as covariates of no interest to improve statistical sensitivity. Null events were not explicitly modeled, and therefore constituted an implicit baseline.N = 28), using one-sample t-tests. Maps resulting from these group analyses were tested with random-effect model for group analysis using FLAME 180 and thresholded using cluster detection statistics, with a height threshold of z > 3.1 and a cluster probability of p < 0.05, family-wise error corrected for multiple comparisons. Second, between-groups differences in whole-brain activation were tested using non-parametric permutation methods for inference on statistic maps  with 10,000 random permutations of the data. Maps resulting from between-groups analyses were thresholded using Threshold-free cluster enhancement (TFCE) with p < 0.05 corrected for multiple comparisons across the whole brain.For each participant, we computed the following contrast images: (i) To assess reactive inhibition: activation during successful stop-signal trials minus unsuccessful stop-signal trials; (ii) To assess proactive inhibition: a parametric contrast on go trials with the four stop-signal probability contexts  coded as mean-centered probabilities; iii) to assess poker cue reactivity during proactive inhibition: parametric modulation by probability during poker cue go trials minus parametric modulation by probability during neutral cue ; iv) to assess poker cue reactivity during reactive inhibition: successful stop during poker cue  minus successful stop during neutral cue , and unsuccessful stop during poker cue  minus unsuccessful stop during neutral cue . On each set of contrast images, we performed two group analyses. First, whole-brain activations were visualized for the whole sample (Supplementary Materials


The reversible phosphorylation of proteins plays hugely important roles in a variety of cellular processes, such as differentiation, proliferation, and apoptosis. These processes are strictly controlled by protein kinases (phosphorylation) and phosphatases (de-phosphorylation). Here we provide a brief history of the study of protein phosphorylation, including a summary of different types of protein kinases and phosphatases. One of the most physiologically important serine/threonine phosphatases is PP2A. This review provides a description of the phenotypes of various PP2A transgenic mice and further focuses on the known functions of PP2A in bone formation, including its role in osteoblast differentiation and function. A reduction in PP2A promotes bone formation and osteoblast differentiation through the regulation of bone-related transcription factors such as Osterix. Interestingly, downregulation of PP2A also stimulates adipocyte differentiation from undifferentiated mesenchymal cells under the appropriate adipogenic differentiation conditions. In osteoblasts, PP2A is also involved in the ability to control osteoclastogenesis as well as in the proliferation and metastasis of osteosarcoma cells. Thus, PP2A is considered to be a comprehensive factor in controlling the differentiation and function of cells derived from mesenchymal cells such as osteoblasts and adipocytes. Protein phosphorylation plays a cardinal role in regulating many cellular processes in eukaryotes. Protein phosphorylation is the major currency of signal transduction pathways; the specific level of phosphorylation of any given signal transduction protein is reversibly controlled by protein kinases and protein phosphatases. The study of protein phosphorylation and de-phosphorylation has a long history. At the beginning of the 1900s, studies concerning the physicochemical properties of canonical phosphoproteins such as casein in milk and vitellin were first performed.a and phosphorylase b. The enzyme is regulated by AMP; phosphorylase a retains 60% to 70% of its maximal activity in the absence of AMP, whereas phosphorylase b requires AMP for its activity. However, during the enzymatic conversion of phosphorylase a to b, no release of AMP was observed; furthermore, AMP could not be detected in phosphorylase a [a is a phosphoprotein and the conversion of active phosphorylase to its inactive form was shown to involve enzymatic de-phosphorylation of the protein.Later on, seminal work on the activity of muscle phosphorylase led to the concept of protein phosphorylation as a means of regulating enzyme activity. Muscle phosphorylase exists in two forms, phosphorylase rylase a . Later, rylase a ,3,4,5,6.Since these initial discoveries, many studies have shown that reversible phosphorylation of proteins, orchestrated by the interplay of kinases and phosphatases, regulates a majority of the important signaling pathways in all living organisms. In fact, the reversible phosphorylation of proteins represents a fundamental mechanism used by all eukaryotic organisms, with up to 30% of all proteins being phosphorylated at any given time . ProteinPSPs are further classified into three major groups: (1) the aspartate-based phosphatases; (2) metal-ion-dependent phosphatases; and (3) phosphoprotein phosphatases ,13. PSPsHalichondria okadaii [PP2A is one of the most important serine/threonine phosphatases, and is essential for embryonic development, cell proliferation, and apoptosis. PP2A has been reported to occupy ~1% of the total amount of protein in mammalian cells . PP2A is okadaii ,27. OA i okadaii ,28. A st okadaii .Numerous transgenic and knockout approaches have been used to address the function of the PP2A C subunit. Complete loss of PP2A Cα leads to early embryonic lethality at E6.5 in mice , althougPP2A impairment has been demonstrated to be relevant to Alzheimer’s disease (AD). In transgenic mice expressing a dominant-negative PP2A C subunit mutant (L199P), the tau protein is hyper-phosphorylated at Ser202/Thr205 and Ser422 . This ph4-induced chronic liver injury and fibrosis and this protective effect is mediated, at least partially, through impaired TGF-β1/Smad signaling.Hepatic fibrosis is a pathogenic response of the liver that occurs as a result of chronic injury and results in the deposition of large amounts of extracellular matrix (ECM) proteins . ActivatSystemic lupus erythematosus (SLE) is an autoimmune disease that arises due to T cell signaling defects. Increases in PP2A expression and activity in T cells, as well as increased IL-17 secretion, have been reported in patients with SLE ,38,39. TCardiac hypertrophy is a pathological change that occurs in heart disease and it has been demonstrated to be associated with protein phosphatases. In particular, protein phosphatases, including PP2A, have been shown to be involved in cardiac structural remodeling by regulating the phosphorylation status of many cardiac proteins ,42. A caAn important role of PP2A Cα was also reported in the epidermis of mammalian skin, which is a critical organ for maintaining body temperature and which protects animals against dehydration, mechanical stress, and infections . ConditiPP2A Cα has also been shown to be an important factor for spermatogenesis and oocyte meiosis. Mice with a spermatocyte-specific deletion of PP2A Cα were infertile and showed a significant reduction in the size and weight of the testes . DisordeHepatic insulin resistance has been shown to be a critical feature of metabolic disorders such as obesity, type 2 diabetes, and coronary artery diseases . Several3, phorbol ester, or prostaglandin E2 [The effect of PP2A inhibition on bone formation and osteoblast differentiation was studied using OA, a potent inhibitor of PP2A. This compound stimulated alkaline phosphatase (ALP) activity in MC3T3-E1 cells, a mouse osteoblastic cell line . OA alsoandin E2 . Adminisandin E2 . The ALPandin E2 .Many factors, including several transcription factors, regulate osteoblast commitment, differentiation, and function and, sequentially, bone formation. Osterix and Runx2 are essential transcription factors for osteoblast differentiation and bone formation . OsterixAdipocytes and osteoblasts are derived from common progenitor mesenchymal stem cells ,69. As sIn the skeletal system, bone is continuously rearranged through the removal of old bone and the apposition of new bone tissue, processes which are mediated by osteoclasts and osteoblasts ,84. RANKOsteosarcoma is the predominant form of malignant bone cancer, occurring mostly in children ,87. DespIn this review, we have provided a brief overview of protein kinases and phosphatases and then demonstrated that the phosphatase PP2A has a pivotal role in controlling bone formation, in differentiation of mesenchymal cells, and in the malignant properties of osteosarcoma cells, as shown in