However, identification of the biological and physical conditions involved and the related processes remains incomplete. Here we specify Southern Ocean surface–subsurface contrasts using a new tool, the combined oxygen and silicon isotope measurement of diatom and radiolarian opal, in combination with numerical simulations. Our data do not indicate a permanent glacial halocline related to melt water from icebergs. Corroborated by numerical simulations, we find that glacial surface stratification was variable and linked to seasonal sea-ice changes. During glacial spring–summer, the mixed layer was relatively shallow, while deeper mixing occurred during fall–winter, allowing for surface-ocean refueling with nutrients from the deep reservoir, which was potentially richer in nutrients than today. This generated specific carbon and opal export regimes turning the glacial seasonal sea-ice zone into a carbon sink.Reduced surface–deep ocean exchange and enhanced nutrient consumption by phytoplankton in the Southern Ocean have been linked to lower glacial atmospheric CO Lower glacial atmospheric CO2 has been linked to enhanced carbon storage in the Southern Ocean, yet the associated biological and physical mechanisms are poorly understood. Here, the authors combine diatom and radiolarian isotope measurements, and model simulations to investigate surface–subsurface processes. The Δδ30Sirad values were calculated with δ30SiSi(OH)4 values averaged from two different water depth intervals , to cover all possible depth ranges of the included species 4 concentrations. The δ30Sirad fractionation offset calculated in our study is more positive than the fractionation applied in ref. 30Sirad values display an inverse trend to the Si(OH)4 concentrations2930Sirad values of approximately +1.4‰ correspond to lower Si(OH)4 concentrations of 30–45 μM l−1, whereas lower δ30Sirad values of +0.7‰ and +0.8‰ correlate with higher Si(OH)4 concentrations of 67–98 μM l−1, which is comparable to the relationship between δ30Si values and Si(OH)4 concentrations documented for diatoms and sponges.where  species . The obt30SiSi(OH)4 from δ30Si values of radiolarians and diatoms averaged over the Holocene in both cores (Methods and 30SiSi(OH)4 data to δ30SiSi(OH)4 and Si(OH)4 concentrations reported from modern water column studies30SiSi(OH)4 calculation we considered a fractionation of −1.1‰ for diatom δ30Si data30Sirad of −0.8‰ 4 values reconstructed from δ30Si of diatoms and surface–subsurface dwelling radiolarians (>250 μm fraction) are in the range of δ30SiSi(OH)4 values reported from the modern mixed layer (ML) in the Atlantic sector of the SO30SiSi(OH)4 values reconstructed from the δ30Si data in the radiolarian fractions 125–250 μm and >125 μm, which also include species with a deeper habitat, are shifted towards lower values. These δ30SiSi(OH)4 values are in the range of δ30SiSi(OH)4 data and Si(OH)4 concentrations from the Circumpolar Deep Water (CDW)2830Sirad values of −1.2‰ and −1.5‰ leads to realistic seawater Si(OH)4 concentrations, estimates calculated with a fractionation offset of -0.8‰ tend to result in overestimated Si(OH)4 concentration. This is most apparent for the result from the 125- to 250-μm radiolarian fraction (PS1768-8) reaching values comparable to those in modern Northwest Pacific Deep Water30Sirad calculations and their relation to modern Si(OH)4 concentrations point to a similar fractionation in diatoms and radiolarians. This assumption represents a step towards quantification of past Si(OH)4 concentration and its variability in surface and subsurface to intermediate-deeper water.To test the reliability of the available information on diatom and radiolarian fractionation we calculated δ14C data series in the studied cores, the generation of age models for both cores considers the dating strategy and stratigraphic data from a compilation of last glacial sea-surface temperature and sea-ice records from the Atlantic sector of the SODuring the last glacial, core PS1768-8  was positioned in the northern glacial SIZ and core site PS1778-5  was in the area of the glacial winter sea-ice edge (GWIE)3518Odiat and δ18Orad signals display a similar pattern with decreasing values from the last glacial period to the early Holocene  increase overprinting the ice volume signal 18O on samples that contain, besides biogenic silica, also non-biogenic components such as terrigenous minerals and volcanic tephra, may result in lower δ18O values and thus bias the isotopic signal towards freshwater-related values1718Odiat values in core TN057-13 may not only be explained by salinity decrease due to iceberg melting but also by a contribution from δ18O-depleted tephra to the δ18Odiat signal. In contrast, IRD deposition in core PS1768-8 decreases between 18 and 16 cal. ka BP. Thus, the δ18Odiat values show no correlation with IRD . The glacial δ30Sirad values range around −1.1‰ and thus are ∼2.7‰ lower than the diatom values. During the deglacial transition, surface–subsurface δ30Sirad values in the southern core PS1768-8 increase to δ30Sidiat values and remain close to the diatom values during the Holocene . Considering that the δ18Odiat records are not indicative of significant freshwater supply, we suggest that the stratification is primarily induced by sea-ice melt during spring, as melting sea ice has no significant effect on the oxygen isotopic composition of surface waters30Sidiat and δ30Sirad records reflect stratification in the upper water column, they would point to glacial surface waters with increased silicic acid consumption and subsurface and intermediate deepwaters with higher silicic acid availability. The deglacial convergence between the δ30Sidiat and δ30Sirad records may point to a deepening of the spring–summer ML depth (MLD), leading to the same Si pool for surface–subsurface-dwelling radiolarians (>250 μm fraction) and surface-dwelling diatoms at site PS1768-8. Considering that this interpretation is strongly based on a radiolarian isotope signal obtained from a nearly monospecific >250 μm fraction, we are confident that the δ30Sirad signal represents environmental change rather than fractionation effects.We interpret the glacial offsets between the δ2 rise and a poleward wind field shift in the SO. All model results are based on simulations using the same fully coupled AOGCMTo further evaluate the physical changes associated with sea-ice variations, we re-analysed two model simulations with conditions during the Last Glacial Maximum (LGM)30Si offset  follow a ‘boom-and-bust' life cycle strategy characterized by rapid biomass build-up during favourable growth conditions, succeeded by mass mortality and rapid population decline. Such a productivity regime results in enhanced organic carbon but low biogenic opal export to the deep ocean and thus leads to the decoupling of biogenic carbon and opal export34The combination of proxy data and AOGCM modelling implies that the sea surface of the glacial SIZ and the GWIE, at least in the Atlantic sector, was distinctly stratified during austral spring–summer with a relatively shallow MLD 40–60 m; . Increas50330Sidiat=+1.62‰ to +1.86‰) at the sea surface and high percentages of biogenic opal in the sedimentsFragilariopsis kerguelensis)F. kerguelensis5For the area of the GWIE PS1778-5), modelling suggests even longer-lasting spring–summer stratification compared with the glacial SIZ (PS1768-8) . However, modelli4) availability at the onset of spring–summer production when surface water stratification is suggested to develop. A similar winter mixing process between ML, Winter Water and CDW is also suggested to take place in the modern SO  together with winter sea-ice expansion33 SO refs , 30. Dur SO refs .4 compared with modern conditions. The δ30Sidiat values at both studied sites point to similar isotopic compositions of the glacial ML and the modern ML (30SiSi(OH)4 signal that can be related to surface–subsurface conditions (fraction >250 μm) is close to modern δ30SiSi(OH)4 values reported from the nutrient replete Winter Water and CDW in the Atlantic sector south of the Antarctic Polar Front. In contrast to the Holocene, the glacial radiolarian-derived δ30SiSi(OH)4 values from the fractions 125–250 μm and >125 μm, which reflect intermediate and deeper water conditions as well, are distinctly lower. These lower values fall in the range of δ30SiSi(OH)4 values reported from the modern deep Northwest Pacific (approximately +0.5‰), which are related to the highest Si(OH)4 concentrations observed in the World Ocean (∼160–180 μmol l−1)30SiSi(OH)4 values and thus higher glacial Si(OH)4 concentrations in SO intermediate deepwaters compared with the Holocene.Amplification of the nutrient injection into the glacial surface ocean may stem from the presence of a deep reservoir that was more enriched in Si(OH)odern ML . However4 concentrations in glacial circumpolar deep waters may be challenged by sponge spicule-based δ30Si records from the Scotia Sea, interpreted to indicate that the glacial deep Si(OH)4 concentrations were not different from modern conditions30Si values (−3‰ to −3.5‰) and thus are in a range where the application of this proxy to sponge spicules is prone to larger uncertainties30Si record from the area straddled by the Subtropical Front ODP1089, , indicatr column , the norr column . This is2 enriched30Si record from the Subantarctic Atlantic 4 concentrations)4 export would support the hypothesis that an expansion of Si(OH)4-enriched Antarctic Bottom Water was the source for maximum opal fluxes (diatom blooms) in the coastal upwelling area off northwest Africa during the last deglaciationA glacial SO trapping nutrients more efficiently than at present is consistent with the scenario of an Antarctic deep water body, whose age relative to the atmosphere was more than two times older than during the Holocene, and which was presumably COODP1089,  indicate30Sidiat and δ30Sirad records reflects a deepening of the spring–summer MLD as proposed above, the MLD deepening would coincide with increased biogenic opal rain  during a time of enhanced ventilation and maximum biogenic opal export suggest that the supply of silicic acid exceeded the consumption by diatoms during this time interval. This points to the injection of nutrient-rich deep waters into the euphotic zoneThe glacial–interglacial transition is characterized by successive changes, starting with the retreat of the sea ice that is accompanied by an increase in opal sedimentation between 18,000 and 16,000 years ago . This ispal rain . Owing tpal rain , we specinterval . These δ30Si, which can be related to modern ML conditions in the Atlantic sector of the SO (30Sidiat and δ30Sirad data from surface sediments (assumed to reflect modern conditions) in the study area  as recorded by diatom and surface–subsurface radiolarian (>250 μm) δf the SO . The Holudy area .2 release from the deep SO, providing a direct link to the coinciding increase in atmospheric CO2  and a poleward shift of the Southern Westerlies wind belt by 3°  in addition to intercore correlation based on different parameters. The AMS14C dates were converted to calendar years and presented as cal. ka BP (103 years before present). Parameters used for intercore correlation include the abundance pattern of the radiolarian Cycladophora davisiana and the diatom E. antarctica, together with foraminiferal oxygen isotope records, if available. Correlations were performed with AnalySeries 2.0 (ref. 14C dates obtained from 12 cores from the study area14C dates from PS1768-8) and their definition are presented in 14C dates or δ18O data, we are confident that our age model is robust enough to allow for appropriate documentation of the environmental development from the last glacial into the present interglacial. According to our age models, the summer SST and WSIC began to shift towards Holocene values between 18 and 16 cal. ka BP  using specific sodium polytungstate solutions. The separation of radiolarians from diatoms and sponge spicules is accomplished through several sieving and settling steps combined with ultrasonic treatment. Our tests show that after ultrasonic treatment radiolarians are still intact, whereas diatoms break up and can be removed through sieving. Repetitions of ultrasonic treatment and sieving steps lead to the separation and enrichment of radiolarians and diatoms in different size fractions. For isotope determinations, we use the pure 10–40 μm diatom fraction (both cores), the >250-μm and the 125- to 250-μm pure radiolarian fraction for core PS1768-8. As there was not enough material, we could only use one radiolarian fraction (>125 μm) for core PS1778-5 and one radiolarian fraction (>250 μm or >125 μm) for each surface sediment sample  for all used working standard materialsσ)  refs , 66.18O signal towards lower values172 contents ranging between 98.5% and 99.5% , and 97.9% and 99.8% (energy-dispersive X-ray spectrometry)  can bias, especially the δrometry) .30Si signalE. antarctica and T. lentiginosa, and are not affected by dissolution (Rhizosolenia sp.) confirms the excellent preservation of the diatom assemblage  and T. lentiginosa making up between 70% and 98%, and 78% and 97% of the species composition in the extracted diatom fractions of PS1768-8 and PS1778-5, respectively  that are not or only rarely included in the 10–40 μm diatom fraction do not affect the isotope signal.For the isotopic measurements, we used a pure diatom fraction (10–40 μm) for the representation of surface-water conditions. This fraction mainly consists of the species ectively . The amoal shift . Small-sA. antarctica, which accounts for >90% of radiolarians in this fraction, and S. glacialis (adult forms), which ranges between 1% and 10% in this fraction. As different radiolarian species live in different water depths, we used data from a plankton study in the Atlantic sector of the SO  that occur in water depths >400 m  than the δ30Sirad values from the >250-μm fraction from core PS1768-8 , we segregated the 125- to 250-μm fraction from core PS1768-8 to get more information about this latitudinal difference in the δ30Si signature. The δ30Sirad measurements from this fraction show distinctly lower values  than the δ30Sirad values from the >250-μm fraction. The fraction 125–250 μm also includes deeper dwelling radiolarians similar as in the >125-μm fraction from core PS1778-5. This suggests that the presence of deeper dwelling radiolarians shifts the δ30Si signal to lower values. C. davisiana, a species typical for glacial assemblages, is not included to the fractions >125 μm because of its small size, which impedes a potential impact of this species on glacial results.For the isotopic measurements on radiolarians, we used three radiolarian fractions to document surface–subsurface and intermediate deepwater conditions. In core PS1768-8, we measured the >250 μm fraction, which is composed of two radiolarian species:  SO ref. . Both spThe estimation of Holocene and glacial silicic acid changes were carried out as follows:30Si values of the diatom (10–40 μm) and radiolarian fractions  for the Holocene  and the last glacial period  were calculated 4 values for the Holocene and last glacial period were calculated using the formula:2. Based on the average diatom and radiolarian δ30SiBSi is the silicon isotope composition of biogenic silica (diatoms or radiolarians), δ30SiSi(OH)4 is the silicon isotope composition of the input sea water 4 values were related to δ30SiSi(OH)4 values and Si(OH)4 concentrations from different water masses reported from modern water-column studies202830SiSi(OH)4 values reflect a rather broad range in Si(OH)4 concentrations (30SiSi(OH)4 values for the diatoms and different radiolarian fractions are in the range of δ30SiSi(OH)4 values of specific water masses and reflect their range in Si(OH)4 concentrations20283. The reconstructed δtrations . In spitWSIC (%) was estimated from the diatom assemblage composition preserved in the sediment records using the transfer function technique. For our study we selected the estimations obtained with the Imbrie and Kipp transfer function method using a setup with 172 reference sites, 28 diatom taxa/taxa groups, logarithmic-transformed diatom data, quadratic regression and a three-factor model with a root mean square error of prediction of 7.3% ref. . Similar2 increase from 180 to 240 p.p.m.v. has been applied. Both experiments have been integrated for 600 years. All figures show climatological mean characteristics averaged over a period of 100 years at the end of each simulation.For our simulations we use the experimental settings of the LGMW simulations in ref. How to cite this article: Abelmann, A. et al. The seasonal sea-ice zone in the glacial Southern Ocean as a carbon sink. Nat. Commun. 6:8136 doi: 10.1038/ncomms9136 (2015).Supplementary Figures 1-13, Supplementary Tables 1-12 and Supplementary References


Carbon isotopic fractionation occurs during SOM decomposition, which leads to 12C to enrich in the released CO2 while 13C to enrich in the residual SOM. Understanding the isotope fractionation has been demonstrated to be helpful for studying the global carbon cycle. Soil and litter samples were collected from soil profiles at 27 different sites located along a vertical transect from 1200 to 4500 m above sea level (a.s.l.) in the south-eastern side of the Tibetan Plateau. Their carbon isotope ratios, C and N concentrations were measured. In addition, fiber and lignin in litter samples were also analyzed. Carbon isotope fractionation factor (α) during SOM decomposition was estimated indirectly as the slope of the relationship between carbon isotope ratios of SOM and soil C concentrations. This study shows that litter quality and soil water play a significant role in isotope fractionation during SOM decomposition, and the carbon isotope fractionation factor, α, increases with litter quality and soil water content. However, we found that temperature had no significant impact on the α variance.Decomposition of soil organic matter (SOM) plays an important role in the global carbon cycle because the CO The CO2 released from soil respiration enriches 12C while the residual SOM enriches 13C, relative to the substrate, because of carbon isotopic fractionation during SOM decomposition1234562 because the released CO2 finally goes into the atmosphere. Scientists who study global change incorporate carbon isotope data for tropospheric CO2, derived from an international network of stations, into atmospheric circulation models. This step is used to calculate global carbon balance and to analyze atmospheric carbon source/sink positions and quantities89102 in their studies of global carbon cycling. In addition, it has been demonstrated that adding soil carbon isotope variations to carbon-dynamic models provides tighter constraints on certain model parameters having biological and environmental significance124-plant origins and expansions in geological time that use carbon isotope records of ancient terrestrial sediments614151617Soil organic carbon is the largest pool of terrestrial ecosystem and greatly affects global carbon cycling. The COIt is well known that environmental and biotic factors affect the decomposition rate of organic matter131920211213231225272829303132333121325in situ, the C/N ratio of litter depended on the vegetation types and plant species. The C/N ratio increased up to an elevation of 3600 m and then decreased at higher elevations (4 species (located below 1600 m) and alpine frigid meadow vegetation (located at 4200–4600 m) had the lowest C/N ratios.The C/N ratio of litters varied greatly and ranged from 8 to 109 . Since levations . This obThe woody plants including trees and the shrubs had much higher lignin contents than the herbaceous plants . This al13CSOM with soil depth. 13CSOM increase with depth was not regularly observed in these soil profiles  of the total variance. Considering that there are close relationships (collinearity) among variables, for examples, C/N ratio vs. lignin content (p < 0.001), W1 vs. W2 (p < 0.001), and MAT vs. MST (p < 0.001), a stepwise regression  was run with forward direction , The result showed that only two variables, C/N and W1 entered the models, suggesting that they were the most significant influential factors. This regression also shows that C/N ratio of litter displayed a greater effect on α than W1 because C/N ratio entered the model earlier than W1.Initially, a series of bivariate correlation analyses were conducted to preliminarily discover the effects of different environmental and biotic factors on fractionation factor α. OLS estimation is based on the data with characteristics of normal distribution and can describe the influence of independent variables on the mean dependent variable. For the data with characteristics of non-normal distribution, OLS no longer has the advantage of the best linear unbiased estimation (BLUE). Consequently, it is not able to effectively describe the influence of independent variables on the minimum and maximum of range of dependent variables. Instead, quantile regression overcomes the limitations of the OSL estimation and can more precisely reflect the effects of independent variables on dependent variables at different quantiles. Thus, in this study quantile regressions were run to exam the dependence of α on environmental and biotic factors in detail. It was also based on the consideration of close relationships (collinearity) among variables, in the quantile regression only three variables, C/N, W1 and MAT were taken as the predictors. The results showed the superiority of the quantile regression . This pret al. (1996)et al. (1993)13C enrichment occurred in soil where evergreen trees were located, which presumably had a lower litter quality. They further reported that a great 13C enrichment occurred in deciduous forests, which were expected to have a higher litter quality. Garten et al. (2000)13CSOM in the Southern Appalachian Mountains, USA, and found that less vertical change in δ13CSOM was associated with poorer litter quality (higher C/N ratios). The 13C enrichment and fractionation factor are not the same parameter, but generally, 13C enrichment is positively proportional to α. Thus, the two previous investigations also suggest increasing α with litter quality.This study showed that α values tend to decrease with higher C/N ratios, higher lignin contents, and lower cellulose contents. This suggested that an increase in α is associated with higher litter quality . Although at present no direct observation of a correlation between α and litter quality has been reported, two previous studies may indirectly support our finding. Ågren 2 and H2O1213192324224041During decomposition, microbes assimilate a part of the existing organic carbon to build their bodies, and remaining organic carbon is oxidated into CO* are the rate constants of the decomposition reaction involving 12C-substituted organic matter (or molecule) and 13C-substituted organic matter (or molecule), respectively. Since the decomposition rate of organic matter increases with decreasing C/N ratio and lignin content and increasing cellulose content, both the rate of decomposition involving 13C-substituted organic matter and the rate of decomposition involving 12C-substituted organic matter also increase. However, because 13C-substituted organic matter (or molecule) has a higher activation energy than 12C-substituted organic matter (or molecule), the decomposition reaction involving 13C-substituted organic matter increases its rate less than the reaction involving 12C-substituted organic matter. This feature causes α to increase with decreasing C/N ratio and lignin content and with increasing cellulose content of litter.where k and ket al. (2001) observed a greater hydrogen isotope fractionation for toluene degradation in growth experiments with the aerobic bacterium P. putida mt-2 and a less fractionation in toluene degradation by the anaerobic bacteriaThe second explanation for a change in α with litter quality is that the properties and compositions of microbial decomposer communities are associated with litter quality43444345et al. (2004) did not observe a significant carbon isotope fractionation during mineralization of 1,2,4-trichlorobenzene by the aerobic strain Pseudomonas sp. P51, which used a dioxygenase for the initial enzymatic reactionDehalococcoide sp.High soil water content could lead to the formation of an anaerobic environment that limits microbial growth and decomposition of organic matter. However, this study shows that higher soil water content is related to a greater carbon isotope fractionation. The effect of water availability on isotope fractionation is also associated with compositions of microbial communities. Microbial communities in aerobic environments differ from those in anaerobic environments. As mentioned above, different microbes could use different metabolic pathways to decompose the same organic compound, thus, aerobic microbes could produce a different isotope fractionation from that produced by anaerobic microbes. For example, Griebler et al. (1981) found that undefined cultures of methane-oxidizing bacteria displayed greater carbon isotope fractionation at 30 °C than 11.5 °CFor a pure chemical reaction, the magnitude of the kinetic fractionation factor α is dependent on temperature and difference of activation energy (ΔQ) between heavy and light isotopically substituted molecules of the reactant47504445The quantile regression showed that fractionation factor α at high quantiles was independent of soil water and MAT, suggesting that a great isotope fractionation during SOM decomposition was associated with high litter quality which positively influenced α variance during decomposition . Organic13C profile solely by fractionation of organic matter during decomposition and ignored the other hypotheses such as different isotopic signature of root litter compared to surface litter or temporal changes of isotope composition of vegetal inputs progressively incorporated into the soil13CSOM data. 3) The soil water contents used in this study were measured in the dry season, while fractionation during organic matter decomposition is dependent of long-term soil water conditions. Thus, further studies are needed in the regard.Although the multiple regression of α against 7 variables including C/N, lignin, cellulose, W1, W2, MAT and MST is highly significant, only 36% of the α variance can be explained by these environmental and biotic factors. Three potential reasons were responsible for such a low amount of explanation. 1) In this study, we calculated fractionation factor α of each soil profile based on the approach of Poage and Feng (2004)13C values did not display differences among the bulk individual, leaf, stem and root in our other study conducted recently on 22 C3 plants and 6 C4 plants (unpublished). 2) A previous investigation conducted in the same study area showed that the mean δ13C difference between 0–5 cm soil layer and vegetation was very big, 2.87‰, while the mean δ13C differences between 0–5 cm and 5–10 cm and 10–20 cm soil layer were very small, 0.17‰ and 0.62‰, respectively13C induced mainly by the δ13C decrease in atmospheric CO2 since the industrial revolution. In present study, Δδ13CSOM in 13C difference between mineral soil samples and the surface mineral soil (0–5 cm depth), thus, the effect of δ13C temporal changes of plant inputs on the α calculation should be small and could be neglected. On the other hand, all α values obtained were very small with an average of 1.00118. If the temporal changes of plants δ13C contained in the α calculation, the α values obtained will be probably negative, which would be inconsistent with the actual situation.Although there were some sorts of limitations mentioned above, we are fairly confident that the α values obtained in current study reflect the actual values of the isotope fractionation factor during organic matter decomposition in the ecosystem studied. This confidence is based on the following two facts: 1) the average δIn conclusion, this study shows that the magnitude of isotope fractionation during SOM decomposition was related to biotic and environmental factors. Litter quality and soil water content both had positive impact on α whereas temperature displayed no effect.Mount Gongga is located in the southeastern side of the Tibetan Plateau . There are remarkable differences in terrain and climate between the eastern and western slopes of this area. We selected the eastern slope of Mount Gongga as a study site because it consists of many climate types, diverse ecological systems, and stable vegetation types ranging from tropical, subtropical to cold zone, and relatively little human disturbance. The eastern slope belongs to an alpine gorge landform. The altitude of the eastern slope of Mount Gongga varies from 1100 m a.s.l.  to 7600 m a.s.l., and its climate is warm and dry at low elevations and cold and moist at high elevations. On the slope, temperature decreases and precipitation may increase with increasing altitude; this feature is based on the records of two meteorological observatories on the slopeAn intact and continuous vertical vegetation spectrum can be observed along the eastern slope of Mount Gongga. It consists of subtropical evergreen broad-leaved vegetation , evergreen broad-leaved forests, and deciduous broad-leaved forests), temperate coniferous and broad-leaved mixed forests (2200–2800 m), frigid dark coniferous forests (2800–3600 m), alpine subfrigid shrub and meadow vegetation (3600–4200 m), alpine frigid meadow vegetation (4200–4600 m), alpine frigid sparse grasses and a desert zone (4600–4800 m), and a high-altitude alpine ice-and-snow zone (>4900 m). The vertical distribution of soil on the eastern slope of Mount Gongga is also very pronounced, and a continuous soil sequence occurs from 1100 m to 4900 m. It consists of yellow-red soil (luvisols) (<1500 m), yellow-brown soil (luvisols) (1500–1800 m), brown soil (1800–2200 m) (luvisols), dark-brown soil (luvisols) (2200–2800 m), dark-brown forest soil (luvisols) (2800–3600 m), black mattic soil (cambisols) (3600–4200 m), mattic soil (luvisols) (4200–4600 m), and chilly desert soil (cryosols) (>4600 m)2 area. All aboveground litters within a plot were collected, and then, a soil profile was dug to the weathered rock. The depth of a soil profile depended on the depth of the weathered rock, and most profiles had the depth of 40 cm to 50 cm. In total, 27 sites with 75 plots and 75 soil profiles were sampled along the transect. Organic layers above mineral soil were defined as “litter.” Depth zero refers to the top of the mineral horizon. Litter samples (0.25 m2) were separated into one to four layers, depending on the humus type. Layers were separated and defined by visual aspect according to Kubiena (1953)A vertical transect spanning from 1200 m a.s.l. to 4500 m a.s.l., across five vegetation types and seven soil types, was set on the eastern slope of Mount Gongga. In August 2004, samples  were collected along the transect at intervals of about 100 m. The method of plant sampling was described in previous papers54Soil water content for each of three layers  was determined by comparing the weight of wet and dry soils. Wet soil, the intact natural soil, was oven-dried at 105 °C until the weight did not change anymore.13C and C concentration of SOM were determined on a DeltaPlusXP mass spectrometer  that was coupled with an elemental analyzer in continuous flow mode. The elemental analyzer  combustion temperature was 1020 °C.Soil was oven-dried at 50 °C for 24 h; afterward, stones and plant residues in soil were removed; finally, soil was ground and filtered through a 2 mm sieve. About 3 g of soil consisting of particles less than 2 mm in diameter was immersed by excessive HCl (1 mol/l) for 24 h to remove carbonate, and then washed to neutrality by distilled waterδ13C and soil C concentrations were less than 0.2‰ and 0.1%, respectively.The carbon isotopic ratios are reported in standard notation, relative to the V-PDB standard. The standard deviations for measurements of soil The litter samples (L1) were oven-dried at 65 °C and ground into a fine powder. The measurements of C and N concentrations were conducted on an elemental analyzer . The standard deviations for measurements of litter C and N both were less than 0.1%.Fiber is the insoluble residue in litter after removing fat, starch, protein, and sugar by acid detergent. It includes cellulose and lignin. Lignin is the insoluble residue after dissolving fiber by sulfuric acid.2. The fiber content (%) was calculated by the following Fiber was obtained through the following steps. The first step was to pour 100 ml of hot acid detergent in a beaker with 1 g of litter (previously ground and sieved through a 2 mm sieve), covered the condensing ball, opened the cooling water, quick heated the beaker to a boiling state, and then maintained boiling for 60 min. The second step was to pour the solution into a filter crucible and then vacuumed and filtered the solution so that all acid was removed. The third step was to wash the residues left in the filter crucible two times with 40 ml acetone and then filter the solution until the filtrate was transparent. Each wash lasted 3–5 min. The final step was to place the filter crucible with residues into a ventilate cabinet until all of the acetone evaporated, dried the filter crucible with residues for 4 h at 105 °C, and then weighed the filter crucible with residues and recorded the mass. We denoted the recorded mass as m1 is the crucible mass, and m2 is the total mass of the crucible and residue.where m is the sample mass (1 g in this measurement), m−1 sulfuric acid was poured into the beaker, and let the acid digest for 3 h at 20–25 °C. The second step was to pour the solution into a filter crucible, vacuum and filter the solution so that all of the acid was removed, and then repeatedly washed the residual material with hot water until its pH equaled 7. The residue was lignin, and the amount of cellulose was the difference between the fiber and lignin amounts.Lignin was obtained through the following steps. The first step was to place the above residue into a 50 ml beaker, then 12.0 mol Lα value means a greater fractionation. In Poage and Feng (2004)α during decomposition of organic carbon was defined asThe isotope fractionation factor α indicates the degree of isotope fractionation; a larger RSOM and RCO2 are the 13C/12C ratios of organic carbon (substrate) and respired CO2 (product), respectively.where 13CSOM of soil profiles. It must be noted that only the soil profiles from sites with constant C3 or C4 vegetation can be used to do the calculation. The first step to obtaining α value of each soil profile was to calculate the δ13C difference (Δδ13CSOM) between mineral soil samples and the surface mineral soil (0–5 cm depth). The second step was to calculate ln(ρ/ρ0), where ρ0 is the C density of the surface mineral soil, and ρ denotes the C density of mineral soil samples13CSOM and ln(ρ/ρ0). Finally, α is calculated from the slope of the following linear equationIn this study, we calculated the carbon isotope fractionation factor α of decomposing organic matter by using the data of δEcologists often use isotope discrimination, ε, to describe fractionation of a biochemical process:Rp is the 13C/12C ratio of the product (CO2) and RS the source (substrate) ratio. Comparing where In this study, a series of bivariate correlation analyses were first conducted to preliminarily exam the effects of different environmental and biotic factors  on fractionation factor α, then a stepwise regression of α vs. the 7 variables was run with forward direction  so that the most important influential factors could be determined. In order to effectively describe the influence of environmental and biotic variables on the minimum and maximum of range of fractionation factors, quantile regression of α vs. C/N, W1 and MAT was carried out. We used the statistical software SPSS 11.0  for the analyses of correlation and stepwise regression, and the Stata/SE120 for Windows  for the quantile regression.How to cite this article: Wang, G. et al. Effects of environmental and biotic factors on carbon isotopic fractionation during decomposition of soil organic matter. Sci. Rep. 5, 11043; doi: 10.1038/srep11043 (2015).


There is an ongoing debate whether stroke patients presenting with minor or moderate symptoms benefit from thrombolysis. Up until now, stroke severity on admission is typically measured with the NIHSS, and subsequently used for treatment decision.Acute MRI lesion volume assessment can aid in therapy decision for iv-tPA in minor stroke.We analysed 164 patients with NIHSS 0–7 from a prospective stroke MRI registry, the 1000+ study . Patients were examined in a 3 T MRI scanner and either received (n = 62) or did not receive thrombolysis (n = 102). DWI (diffusion weighted imaging) and PI (perfusion imaging) at admission were evaluated for diffusion - perfusion mismatch. Our primary outcome parameter was final lesion volume, defined by lesion volume on day 6 FLAIR images.The association between t-PA and FLAIR lesion volume on day 6 was significantly different for patients with smaller DWI volume compared to patients with larger DWI volume (interaction between DWI and t-PA: p = 0.021). Baseline DWI lesion volume was dichotomized at the median (0.7 ml): final lesion volume at day 6 was larger in patients with large baseline DWI volumes without t-PA treatment . Conversely, in patients with larger baseline DWI volumes final lesion volumes were smaller after t-PA treatment . However, this did not translate into a significant difference in the mRS at day 90 (p = 0.577).Though this study is only hypothesis generating considering the number of cases, we believe that the size of DWI lesion volume may support therapy decision in patients with minor stroke.NCT00715533Clinicaltrials.org  Thrombolysis has become standard therapy in the treatment of acute ischemic stroke and is used within a time frame of ≤4.5 hours in Europe since ECASS 3 Moreover, there is disagreement regarding the outcome in minor stroke patients with reports of excellent outcome at 3 months follow-up without any intervention MRI has been suggested to identify patients with minor stroke as well as point out those who might suffer a recurrent stroke and might therefore benefit from thrombolysis. Rajajee et al. This leaves minor stroke patients who show no vessel pathology but are considered as possibly benefitting from thrombolysis.It also has been shown that a mismatch volume of more than 10 ml is predictive of lesion progression and early neurological deterioration Furthermore, to save time, especially at the end of the mandated time window it might be necessary to shorten the MRI imaging protocol to haemorrhage sensitive sequences (T2*) and diffusion weighted imaging (DWI).Therefore, we aimed to evaluate the potential of DWI at admission in patients with low/moderate NIHSS in facilitating therapy decision towards thrombolysis by comparing minor stroke patients who did and did not receive t-PA.The protocol for this trial and supporting CONSORT checklist are available as supporting information; see From 11/2008 until 6/2012 we included 190 patients with ischemic stroke from the observational 1000+ study, registered at clinicaltrials.org NCT00715533.Written informed consent was obtained from all patients. The study design (1000+ study) was approved by the ethics committee of the Charité - Universitätsmedizin, Berlin (EA4/026/08).2, 6 different directions), bolus – track perfusion imaging (PI) , a fluid-attenuated inversion recovery sequence (FLAIR)  and a 3 dimensional time-of-flight magnetic resonance angiography (MRA) (TR/TE/flip angle/field of view/slice thickness: 22 ms/3.9 ms/20°/162*200/0.7 mm). For the perfusion measurements a bolus of 5 ml Gadovist was administered, followed by a saline flush both at a flow rate of 5 ml/s.Data acquisition was performed on a 3 Tesla MRI scanner . The imaging protocol included a diffusion weighted imaging (DWI) , regional cerebral blood volume (rCBV) and mean time-to-peak (MTT) maps with the latter used for further analysis. Regions of interests (ROI) were manually drawn on DWI, MTT – maps and FLAIR day 6 images. Lesion volumes were calculated from ROIs, acute absolute mismatch volume (MTT volume – DWI volume) and mismatch ratio (MTT volume/DWI volume) were assessed.All continuous variables were checked for normal distribution  before using parametric tests. Otherwise non-parametric statistical tests were applied or the variables were transformed before analysis to reduce skewness in distribution. The Mann-Whitney test was employed to compare differences between groups for quantitative non-normally distributed outcomes. To assess differential treatment ((iv) t-PA) effects for patients with different DWI volume on admission with regard to FLAIR volume on day 6, a regression analysis was performed using log-transformed values for lesion volumes with log-transformed FLAIR volume as outcome. Log-transformation was performed to overcome the skewed distributions. A regression analysis was also used to evaluate the association between vessel status and FLAIR volumes on day 6. A level of α = 0.05 was considered significant. No adjustment for multiple testing was applied.For exploratory purposes we used a median split of 0.7 ml to assess the effect of thrombolysis on DWI and FLAIR volumes. All statistical analyses were performed using SPSS version 20.The inclusion criteria for this study were as follows:Visible lesions on DWI at admission, since it could be demonstrated that only 4 out of 299 patients with negative DWI images had perfusion deficits, indicating ischemia One-hundred-and-sixty-four out of 190 patients with minor/moderate stroke were considered for further analysis.The reasons for exclusion were incomplete examinations (n = 7), faulty entry to database (n = 5), unknown symptom onset (n = 5), onset>9 hours (n = 4), mechanical thrombus extraction (n = 2), no visible DWI lesion (n = 1), one haemorrhage and one patient with postictal edema.The reasons for patients within the time window of less than 4.5 hours (n = 50) for not receiving t-PA were as follows:Rapidly improving symptoms (n = 24), patients considered “too good” to treat (n = 6), infarcts of varying ages (n = 4), oral anticoagulation (n = 3), haemorrhagic transformation (n = 1), one patient had occlusions of both vertebral arteries and the basilary artery, one had a clear demarcation on FLAIR and the last one had haemoptysis. In 9 patients no further information on the reasons for exclusion from t-PA therapy could be obtained.Detailed patient characteristics are given in There were no significant differences in baseline variables between patients treated with iv t-PA and those not treated, with the exception of time between onset and MRI examination with shorter delays in treated patients, median:105 minutes (IQR 79–145 minutes) compared to 233 minutes (IQR 122–380 minutes) in untreated patients (p<0.001). There was also a difference in NIHSS values at admission: median NIHSS 4 (IQR 2–5) in iv t-PA treated patients compared to 2 (IQR 1–4) in the non iv t-PA group (p = 0.002). No significant difference for mRS at 3 months follow-up was found between groups (median 1 (IQR 0–2)) (p = 0.577).Though no significant differences between the median DWI volume at admission and FLAIR volume on day 6 could be demonstrated, the regression analysis showed a significant interaction of DWI volume and thrombolysis on FLAIR day 6 volumes as outcome parameter (p = 0.021) , table 2In this pilot study we found a significant association between infarct volume changes and thrombolytic treatment. Treatment effect in terms of smaller infarct growth was stronger in patients with larger DWI volumes compared to those with smaller DWI volumes. This argues for baseline DWI volume as useful parameter in assisting therapy decision towards or against thrombolysis in minor stroke patients.There is still considerable uncertainty regarding therapy decision resting upon clinical scales like the NIHSS alone. Many attempts have been undertaken to assess non-isolated symptoms as defining variables in minor stroke (NIHSS ≤6) There have also been many efforts to establish imaging variables capable of predicting deficit and severity of disability due to stroke, therefore aiding therapy decisions. Among those the most common imaging parameter is the perfusion – diffusion mismatch to detect potentially salvageable tissue. Recently, for minor stroke, a volume of mismatch above 10 ml was found to be associated with infarct growth and neurological deterioration Other studies describe correlations between acute DWI and PI lesion volumes and acute and chronic stroke scales Another strong relationship was reported between infarct extent and location providing a good estimate of neurological deficit within 3 months of stroke onset The association between the extent of infarct growth and outcome in patients with moderate/severe stroke symptoms has already been proven As a novel finding in our study, infarct growth was attenuated by thrombolysis in patients with larger DWI infarcts. However, within our small cohort the median mRS at day 90 did not differ significantly in treated and untreated patients, hence, no clear prediction regarding long term outcome can be drawn. Likewise, Urra et al., in a study cohort of 203 patients did not find significant differences in mRS on day 90, but did find a decrease in the mRS in the ordinal regression analysis The lack of a significant difference in long term outcome may also be explained by the limited capacity of the mRS in depicting post stroke disorders like fatigue, depression We found no association between vessel status and outcome, but untreated minor stroke patients with vessel occlusions showed, at least for the short term, an increase in infarct volume compared to iv t-PA treated patients, therefore pointing to the effect of thrombolysis. This observation is shared by others The limitation of our study is clearly the small number of patients, indicating that this study is underpowered to sufficiently predict long term outcome and thus may be considered as only hypothesis generating. Using a median split of baseline DWI volume at 0.7 ml seems to be arbitrary at the moment, however, in dichotomizing the data the influential effect of t-PA treatment could be illustrated. Though, using this method a loss or overestimation of effect size and power in case of bivariate relationships or analysis of independent variables must be kept in mind The size of baseline DWI infarct volumes can support therapy decision for iv t-PA in minor stroke, in addition to findings of perfusion imaging and NIHSS score. Though, regarding the number of cases, this study must be considered as only hypothesis generating.Checklist S1CONSORT checklist.(DOC)Click here for additional data file.Protocol S1Trial protocol.(DOCX)Click here for additional data file.


This work quantitatively characterizes intrinsic disorder in proteins in terms ofsequence composition and backbone conformational entropy. Analysis of the normalizedrelative composition of the amino acid triads highlights a distinct boundary betweenglobular and disordered proteins. The conformational entropy is calculated from thedihedral angles of the middle amino acid in the amino acid triad for theconformational ensemble of the globular, partially and completely disorderedproteins relative to the non-redundant database. Both Monte Carlo (MC) and MolecularDynamics (MD) simulations are used to characterize the conformational ensemble ofthe representative proteins of each group. The results show that the globularproteins span approximately half of the allowed conformational states in theRamachandran space, while the amino acid triads in disordered proteins sample theentire range of the allowed dihedral angle space following Flory’sisolated-pair hypothesis. Therefore, only the sequence information in terms of therelative amino acid triad composition may be sufficient to predict protein disorderand the backbone conformational entropy, even in the absence of well-definedstructure. The predicted entropies are found to agree with those calculated usingmutual information expansion and the histogram method. Conformational entropy of proteins is a proxy measure of its internal dynamics, which maybe characterized by enumerating the different microscopic structural states involved inatomic motion1272, derived from spin relaxation13151718The conformational entropy of a protein may be characterized in terms of dihedral angles.Neglecting the time-dependent correlation of the dihedral angles may often lead to anupper bound of the value of conformational entropy11Intrinsically disordered proteins may be best represented as a dynamic ensemble ofrapidly interconverting conformations23242627282926This article quantifies the structural disorder of partially/completely disorderedproteins in terms of both sequence composition and backbone conformational entropy,relative to that of the globular proteins. The non-redundant database along with theselected data sets of globular proteins, partially and completely disordered proteins(IDPRs and IDPs) are compiled separately for sequence analysis. MC and MD simulationscharacterize the conformational ensemble of the representative proteins of each group. Asequence analysis of the normalized relative composition for each individual amino acidreveals a considerable overlap between globular proteins and IDPs. However, thenormalized relative composition calculated using amino acid triads is higher for IDPs ascompared to the globular proteins and well demarcated from the region occupied byglobular proteins. The conformational entropy of a disordered protein sequence may beexpressed as the sum of the conformational entropy of the corresponding triads presentin the non-redundant database obeying Flory’s isolated-pair hypothesis. Thusprotein disorder may be predicted from the relative sequence composition only, while thebackbone conformational entropy provides an appropriate measure of this structuraldisorder. The advantage of this method is that it avoids the requirement of extra longsimulations which is not only computationally expensive but also time consuming.25% (Feb 2010release of PDB-select 1992–20093 Å and R-factor≤0.3 are selected from the Protein Data Bank(PDB)4316 chains from 4163 proteins with chain lengths rangingfrom 25 to 1015 residues.The non-redundant database chosen for this study comprised of non-homologousprotein chains with a sequence identity of ≤3 Å. All proteins comprise ofonly single chains without any missing residues (listed in REMARK 465 ofPDB). A sequence similarity of ≤25% and length≥40 residues is applied using PISCES server1917 chains with chain lengths ranging between 40 and1724 residues.A data set of the globular proteins is compiled from the RCSB PDB with X-raycrystallographic structures of resolution≤9508 proteinchains is obtained from the compiled database using PISCES server with theselection criteria of ≤25% and length≥40 residues. Out of these proteins, 138chains with >50% structural disorder  comprise of the Group I data set. The chain lengths of these proteinsspan between 40 to 926 residues.A data set of protein chains with intrinsically disordered protein regions(IDPRs) is selected from the PDB. The disordered regions are characterizedby missing residues in the electron density map of the respective X-raycrystallographic structures. A non-redundant data set of 109 Intrinsically Disordered Proteins (IDPs) is selected fromthe DisProt, i.e., Database of Protein Disorder (Release 6.02)25% and length ≥40residues is applied on these proteins using PISCES server. The final dataset of IDPs comprises of 91 proteins with chain lengths rangingbetween 40 and 1861 residues. The detailed method for theselection of globular, Group I and Group II proteins may be found in Ref.A set of 1A4V). Disordered proteins areselected from two classes: (i) 1CD3, 1F0R and 1MVF, withwell-defined secondary structure coexisting with highly flexible disorderedregions (ii) α-synuclein, which lacks well-defined tertiarystructures and is completely disordered. The representative proteins areselected because of the following reasons: (i) The selected proteinscollectively possess the complete set of 20 amino acids in theirdisordered regions, (ii) All proteins exhibit varying degree of structuraldisorder with 1CD3 having the minimum percentage of disorder content andα-synuclein with maximum disorder content, (iii) Selected proteinshave varying location of disordered regions i.e. at C-terminus of the sequencefor 1MVF, N-terminus of the sequence for 1F0R, in middle regions of thesequence for 1CD3 and throughout the entire sequence forα-synuclein. The three dimensional structures of the ordered regionsof 1CD3, 1F0R and 1MVF are obtained from the PDB, while missingresidues in the disordered regions are modeled with MODELLERConformational ensembles of the representative proteins from different groups aregenerated independently via Molecular Dynamics and Monte Carlo simulations. Therepresentative globular protein is α-lactalbumin, whose crystalstructure is extracted from the PDB  inexplicit-water using AMBER 12 simulation package4210 Å from the protein surface with closenessparameter 1 Å. The charge of each protein isneutralized by adding either Na+ or Cl– depending upon the charge ofthe solvated proteins. The PME algorithm8.0 Å is used for treating thelong-range electrostatic interactions and a 8 Ådistance cutoff is applied for the non-bonded interactions. The hydrogen atomsare constrained to the equilibrium bond length using the SHAKE algorithm0.002 ps. Constant temperature and pressure are controlledthrough Berendsen’s temperature bath with coupling constant of2 ps and barostat with a coupling constant of1 ps, respectively5 ns is thenperformed for each solvated protein at a constant temperature of300 K and a pressure of 1 bar followed by an extended NPTsimulation of 100 ns. The root-mean-square deviation (RMSD)and radius of gyration (Rg) are plotted as a function of thesimulation time for each protein in Molecular Dynamics simulations are performed for each of the representativeproteins -Cα(i + 1)andCα(i)-Cα(i + 2)bond lengths are restricted to3.8 ± 0.15 Å476.0 ± 1.5 ÅMetropolis Monte Carlo simulation is also performed for where,Hαj andHαk arethe normalized hydrophobicities of residuesαj andαk respectively.rj,k is the distance between thesites j and k. The choice of the potential ensures that thehydrophobic-hydrophobic interactions are preferred while polar-polarinteractions are not.where, Qαj andQαk arethe charges on the residuesαj andαkrespectively.nmw(αj)and ncn represents the normalized molecularweight of αj and thenormalized coordination number of the jth site inthe ith conformation respectively. The stericenergy function is chosen such that the residues with high molecular weight ispreferred at sites with low coordination number, while the residues with lowmolecular weight are preferred at highly coordinated sites. For each Monte Carlosimulation, 2000 conformations are randomly selected for each of therepresentative proteins. These conformations for each protein are solvated usingTIP3P water model and energy minimized using AMBER 12. Root-mean-squaredeviation (RMSD) and radius of gyration (Rg) for the selected MCconformations are plotted for each protein in where, Backbone conformational entropy may be evaluated from the probabilitydistribution of the ϕ - ψ dihedral angles of the mainchain of polypeptides108Pi is the fraction of amino acidspresent in the ith bin for a specific range ofϕ - ψ angles of a given peptide segment. For each aminoacid, the distribution of dihedral angles is obtained from the database ofconformations. For the calculation of residuewise conformational entropy,individual amino acids are binned across the specified range of ϕ -ψ angles90 × 90 equallyspaced grids; the height and width of each grid is 4°. Each aminoacid in the protein is classified in a specific grid according to the values ofits ϕ - ψ angles. The correspondingPi value is calculated fromthe fraction of the respective amino acid in that specific grid in the database.The conformational entropy of a protein is calculated from itsPi values as defined in eqwhere 8 Åith residue of a protein, neighbors alongthe sequence  are neglected since contactsformed between these residues are present in the denatured state also with highprobabilityAverage number of two-body contacts is a measure of the residue-residueinteractions present in any protein which discriminates the globular proteinsfrom the disordered ones. A pair of non-hydrogen atoms is considered to be incontact when they are separated by a distance less than1A4V) in The residuewise conformational entropy is calculated using eq Relative composition of the individual amino acids is calculated from the fraction ofthat amino acid present in the data set of Group II proteins relative to that of theglobular proteins. The relative composition of amino acid is given by1 to 20,Pi = Pji denotes the fraction ofjth residue in ithsequence of length ni and the summation is over allsequences in the respective data sets of proteins. The normalized relativecomposition is used to differentiate between the globular and Group II proteinswhich may be expressed aswhere j = R is the total number of residues in a sequence,Δr represents the normalized relativecomposition of rth residue in a sequence in the dataset X for either globular proteins or Group II proteins. 8000) is considered, since theconformational flexibility of a specific amino acid residue is dependent on itsflanking neighbors at the two ends. The normalized relative composition of thesetriads are calculated for each sequence of the globular and Group II proteins. Thecalculation of the normalized relative composition of the triad is similar to thatof the individual amino acids using eqs 203 = 8000). For aminoacid triads, Pji is the fraction of thejth triad in theith sequence and R represents the totalnumber of such triads in the sequences of the data sets for globular and Group IIproteins. It is found that triads HHH, LEH, ALS and VLDare least preferred (except the triads which do not exist in Group II proteins)while triads QPF, PQQ, PHW and QQP are highly preferred in Group IIproteins protein, IDPRs , and IDPs (α-synuclein)respectively. The conformational entropy of each conformational ensemble may becalculated by the histogram method asThe above results confirm that the choice of amino acid triads provides a simple andeffective method to predict disorder in proteins. This may suggest that these triadsencode important information about the stability, flexibility and conformationalentropy of proteins. Thus, the conformational entropy of these triads are calculateddepending on the distribution of ϕ - ψ angles for differentconformational ensembles of the non-redundant database, globular  and is restricted to theα-helix region in the Ramachandran plot, DAT(S = 2.717) populates the α-helix andPP-II helix region, while TAS (S = 2.855)populates α-helix, PP-II helix and β-sheet regions. Thissuggests that the neighboring flanking residues of an amino acid may havesignificant influence on the structural degrees of freedom of that amino acid.Similarly, Proline, which is known to be structurally rigid, may exhibit variedstructural flexibility and conformational entropy as is evident from D and K (REI exhibits the lowestentropy (S = 1.819) while RNI exhibits highestentropy (S = 3.006). X1X2X3),which show higher entropy relative toX1GX3, with 99% confidenceinterval for 2000 bootstrap resampling iterations. The relative entropies of thetriads that exhibit minimum entropy with respect toX1GX3 are given in 1A4V), IDPRs  and IDPs(α-synuclein) using MD and MC generated conformational ensembles. Theratio of the conformational entropy of a specific triad in a data set of proteins tothe corresponding conformational entropy of the triad in non-redundant database iscalculated and the probability distribution of this ratio is plotted in where  D and K . Figure 60 ns, 80 ns and100 ns. The probability distribution of this ratio is plotted in60 ns and 100 ns MDtrajectory, 80 ns and 100 ns MD trajectoriesdepict a similar distribution of the conformational entropy for both partially andcompletely disordered proteins. The position of the maximum is coincident for both80 ns and 100 ns MD trajectories in bothfigures. This implies a 100 ns MD simulation may be sufficient tosample the ϕ - ψ range of the triads in disordered proteins.Recent studies5455100 ns long MD simulation may adequately sample the dihedralangle space of the intrinsically disordered proteins. It is observed that dihedralangles are strongly correlated for IDPs, a few most populated dihedral combinationsmay dominate a major fraction of the entire conformational ensembleThe ratio of the conformational entropy of any triad in the conformational ensemblesof the partially and completely disordered proteins to that in the non-redundantdatabase is calculated for conformational ensembles generated by MD simulations at1A4V), IDPRs and IDPs (α-synuclein) are plotted in LLK, IVE and NKL) in globularproteins span approximately half of the ϕ - ψ region ascompared to the non-redundant data set of proteins. This may be due to the fact thattriads in globular proteins exhibit a propensity for either helices or sheetstructures and hence span limited regions of the Ramachandran space. While the aminoacid triads in IDPRs  and IDPs  populate the entire range spanned by the non-redundant database ofproteins. Since, disordered proteins lack specific secondary structures, triads inIDPRs and IDPs assume all possible ϕ - ψ angles in theallowed dihedral angle space. The triads in IDPRs and IDPs thus obey theFlory’s isolated-pair hypothesisThe ϕ - ψ angles of the selected triads from each ensemble ofconformations of globular (S(i) represents the conformational entropy of theith disordered protein, t is the totalnumber of triads in ith protein sequence andjth triad in the non-redundant database.Similarly for a sequence of a globular protein, the average conformational entropymay be estimated aswhere Mutual information expansion method is used to verify the validity of the resultsobtained from our entropy prediction method. Systematic expansion of entropy inmutual-information terms upto second order may be written as12whereI2,is a measure of the correlation between two degrees of freedom , which denotes the mutual information of the system.S1(xi) andS1(xj) represents the uncorrelatedShannon entropies for xi and xjdihedral angles respectively.S2 is the correlated entropy for the pair of dihedralsxi and xj . For 1A4V,the correlation of ith dihedral withi + 1,i + 2 andi + 3 is found to be 0.07, 0.016and 0.012 per dihedral pairs, respectively, for grids with height and widthof 30°. The correlation between two dihedrals is found to decrease withan increase in the distance between dihedrals along the sequence. Thus, thecorrelation of each dihedral angle is calculated upto the nearest neighbor th dihedral).The conformational entropy predicted using our method (using eqns 9 and10) is compared  and histogrambinning method (a maximum 3.3% difference). Hence, our sequence-based methodprovides fairly accurate estimation of the conformational entropy using the sequenceinformation only, with the nearest neighbor pair correlation.Here,ared see  with thoMC generated conformations for IDPRs and IDPs depict a wider range of ϕ -ψ angles compared to that of the non-redundant database. This is due tothe choice of the coarse-grained potential for MC simulations with less restrictionsimposed in the accessible conformations. Thus this study proposes a method topredict the disorder in proteins from the relative composition of the amino acidtriads including a measure of an average conformational entropy for that sequence,since it may not be feasible to determine the conformational entropy of a largenumber protein sequences, especially for the completely disordered proteins, bysimulations.1A4V, 1CD3, 1F0R, 1MVF andα-synuclein) with a distance cutoff of8 Å. The distribution of two-body contacts for alldata sets of proteins is plotted in 1CD3, 1F0R, 1MVF and α-synuclein, thetwo-body contacts depict a broad distribution, with the peaks matching withrespective ensembles of MD simulation. The broad distribution of MC simulationgenerated ensemble is due to use of the coarse-grained model with lessrestrictions.The lower conformational entropy for globular proteins may be attributed to thehighest number of favorable two-body contacts which are the primary stabilizingfactor for well-defined structures. The two-body contacts are calculated usingnon-redundant database and conformational ensembles generated from MD and MCsimulations respectively .


The purpose of this study was to investigate force variability generated by both the paretic and non-paretic hands during bimanual force control. Nine chronic stroke individuals and nine age-matched individuals with no stroke history performed a force control task with both hands simultaneously. The task involved extending the wrist and fingers at 5%, 25%, and 50% of maximum voluntary contraction. Bimanual and unimanual force variability during bimanual force control was determined by calculating the coefficient of variation. Analyses revealed two main findings: (a) greater bimanual force variability in the stroke group than the control group and (b) increased force variability by the paretic hands during bimanual force control in comparison to the non-paretic hands at the 5% and 25% force production conditions. A primary conclusion is that post stroke bimanual force variability is asymmetrical between hands. Variability abounds when chronic stroke individuals attempt to control force production. Post stroke deficits in bimanual force control are common, especially in activities of daily living . Movement variability arises from both bimanual and unimanual motor actions. However, bimanual variability does not equal the summation of variability from paretic and non-paretic hands.Previous bimanual force control studies demonstrated impaired capabilities post stroke Unfortunately, the above explanations do not answer a critical stroke motor recovery question about bimanual movements: Does force control asymmetry between hands show up in force variability data? Even though previous unimanual force control studies reported higher force variability in the paretic hands than the non-paretic hands This knowledge is important because rehabilitation programs could structure their protocols with a clear understanding of bimanual force control as well as force variability. Earlier bimanual training focused on recovery of bimanual resultant function The University of Florida's Institutional Review Board approved the protocol and informed consent form involved in this study. Prior to beginning testing, all participants read and signed an informed consent.SD = 18.8); 6 females and 3 males] and nine age-matched controls . Additional characteristics of the stroke group follow: (a) impaired hemisphere: 6 left and 3 right; (b) stroke type: 8 ischemic and 1 hemorrhagic; (c) mean time since stroke = 4.6 years (SD = 4.4); and (d) mean hand function score on the Stroke Impact Scale (version 3.0) = 72.2 (SD = 21.4) Volunteers included nine stroke individuals  and (b) force level . The stroke group  showed significantly greater bimanual force variability than the control group . Concerning the force level main effect, the bimanual force variability for the 5% condition  was significantly greater than at the 25% condition .A two-way mixed design ANOVA on the bimanual force variability (CV) revealed two significant main effects: (a) group [F = 6.71; p = 0.004; η2 = 0.30; Moreover, to determine force variability (CV) between two hands during bimanual force control, a three-way mixed design ANOVA on the force variability by each hand was performed. The analysis revealed a significant Group×Hand×Force Level (2×2×3) interaction [p<0.001, r = 0.98, R2 = 0.97; see p = 0.007, r = 0.82, R2 = 0.68; see Determining the force variability contributions of each hand to bimanual force variability involved conducting a linear regression analysis on the three force levels for each group. Analysis of the stroke group's data revealed greater force variability (CV) in the paretic hands than the non-paretic hands. The greater force variability was associated with an increased bimanual force variability at the two lower force levels. For the 5% condition, the bimanual CV equation p = 0.041, r = 0.69, R2 = 0.47; see In contrast, most individuals in the control group produced similar force variability between hands at the two submaximal force levels. At the 50% condition, the control participants showed decreased bimanual force variability. The non-dominant hands force variability values were less than the dominant hands: the bimanual CV equation The purpose of this study was to investigate force variability generated by both the paretic and non-paretic hands during bimanual force control. Analyses revealed two primary findings: (a) greater variability of the combined bimanual forces in the stroke group versus the control group and (b) higher CV in the paretic hands than the non-paretic hands and the control group (non-dominant and dominants hands) at 5% and 25% of MVC.The greater bimanual force variability found in the stroke group than the control group is consistent with previous findings Consistent with our hypothesis, regression analyses for the stroke group revealed that the greater force variability by the paretic hands than the non-paretic hands was strongly associated with an increase in bimanual force variability at the 5% and 25% of MVC. These findings support the supposition that bimanual force control is more affected by the paretic hands control than non-paretic hands at the submaximal target levels. Consequently, quantifying bimanual force control variability for the two lowest MVC conditions (5% and 25% of MVC) provides motor impairment evidence in the paretic hands as well as bimanual motor function Earlier bimanual stroke studies demonstrated less force production by the paretic hands than non-paretic hands and emphasized that restoring similar force production between the hands is an important goal in stroke rehabilitation Motor control performed by healthy individuals shows that one hand is not always equivalent to the other hand when executing bimanual movements. Brain imaging studies revealed that activation of motor areas in the dominant hemisphere was greater than in the non-dominant hemisphere For the 50% level of MVC task, force variability by the non-paretic hands increased as much as the paretic hands for the stroke group and the force variability by the paretic and non-paretic hands was greater than the non-dominant and dominant hands for the control group. Accumulated findings indicate that the higher target level may have increased compensation by the non-paretic hands in stroke survivors. However, given that stroke survivors typically have motor deficits on their ipsilesional side as well In conclusion, the current stroke study clearly revealed asymmetrical force variability between the two hands at 5% and 25% of MVC. Moreover, the greater force variability by the paretic hands than the non-paretic hands increased bimanual force variability. These novel findings suggested that the impaired force control capability in the paretic hands during bimanual force control is a prominent characteristic of motor deficits post stroke. Moreover, the amount of bimanual force variability in stroke survivors reflects their paretic hand control capabilities at the lowest and medium target force levels. An extension of present study will investigate force variability produced by the paretic and non-paretic hands during unimanual and bimanual movement conditions to determine whether the asymmetrical force variability between two hands during bimanual movements is greater than during unimanual movements.


The Eastern oyster, Crassostrea virginica, is the second most valuable bivalve fishery in the US. C. virginica larvae were significantly more resistant to ocean acidification than other North Atlantic bivalves, suggesting it may be a better target for future restoration and aquaculture efforts. Crassostrea virginica , is the second most valuable bivalve fishery in the USA and is sensitive to high levels of partial pressure of CO2 (pCO2). Here we present experiments that comprehensively examined how the ocean's past, present and projected (21st and 22nd centuries) CO2 concentrations impact the growth and physiology of larval stages of C. virginica. Crassostrea virginica larvae grown in present-day pCO2 concentrations (380 μatm) displayed higher growth and survival than individuals grown at both lower (250 μatm) and higher pCO2 levels (750 and 1500 μatm). Crassostrea virginica larvae manifested calcification rates, sizes, shell thicknesses, metamorphosis, RNA:DNA ratios and lipid contents that paralleled trends in survival, with maximal values for larvae grown at 380 μatm pCO2 and reduced performance in higher and lower pCO2 levels. While some physiological differences among oysters could be attributed to CO2-induced changes in size or calcification rates, the RNA:DNA ratios at ambient pCO2 levels were elevated, independent of these factors. Likewise, the lipid contents of individuals exposed to high pCO2 levels were depressed even when differences in calcification rates were considered. These findings reveal the cascading, interdependent impact that high CO2 can have on oyster physiology. Crassostrea virginica larvae are significantly more resistant to elevated pCO2 than other North Atlantic bivalves, such as Mercenaria mercenaria and Argopecten irradians, a finding that may be related to the biogeography and/or evolutionary history of these species and may have important implications for future bivalve restoration and aquaculture efforts.The Eastern oyster,  Many spC. gigas . The surCrassostrea virginica) has a geographical range of 8000 km from Brazil to Canada in the Western Atlantic Ocean, where it inhabits a wide range of salinities (5–30) in coastal zones  grew 40% slower than those exposed to normal CO2 levels. With increasing CO2 levels, C. virginica larvae experience a reduction in calcium content (C. virginica larvae grown with low CO2 levels (280 μatm) yielded slight increases in shell area and calcium carbonate (CaCO3) composition, suggesting that, as was the case for other bivalve species  affect the physiology of larval Eastern oysters, C. virginica. Reductions in the growth and survival at this stage can cause substantial declines in adult populations  were maintained in water baths at 24°C using commercially available aquarium heaters , a temperature ideal for the growth and survival of C. virginica larvae  and remained within ±0.5°C of target values. A gas proportionator system  was used to deliver CO2 gas to seawater treatments at multiple rates. The gas proportionator delivered pre-mixed gases  at flow rates which turned over the volume of experimental vessels several times an hour, ensuring that vessels did not equilibrate with the atmosphere. For experiments, the CO2 gas mixtures were continuously delivered to the bottom of replicated (n  = 4) experimental vessels (detailed below). With continuous bubbling, all treatment carboys remained saturated with respect to dissolved oxygen (∼8 mg l−1). To quantify precise CO2 levels attained in experimental treatments, aliquots were removed immediately before commencing experiments as well as immediately after the conclusion of experiments and analysed immediately using an EGM-4 Environmental Gas Analyzer® (PP Systems) system that quantified total dissolved inorganic carbon (DIC) levels after separating the gas phase from seawater using a Liqui-Cel® Membrane (Membrana). These analyses provided a methodological precision of ±2.6% for replicated measurements of total DIC and provided full recovery (102 ± 3%) of Dr Andrew Dickson's  certified reference material for total inorganic carbon in seawater [Batch 102 = 2013 μmol total DIC (kg seawater)−1]. Levels of CO2 were calculated based on measured levels of total inorganic carbon, pH , temperature, salinity, and first and second dissociation constants of carbonic acid in seawater according to http://cdiac.ornl.gov/ftp/co2sys/). Daily measurements of pH  indicated that experimental vessels maintained a constant pH level throughout experiments (<0.5% relative standard deviation within treatments). Spectrophotometric measurements of pH made using m-cresol purple as described by 2 treatments .This study examined the effects of multiple pCOa larvae . TemperaCrassostrea virginica larvae were obtained from the East Hampton Shellfish Hatchery  within hours of fertilization. Wild broodstock were obtained from the eastern Peconic Estuary , which experiences normoxic and normocapnic levels of oxygen and pCO2 , a modern level (∼380 μatm pCO2), an elevated level (∼750 μatm pCO2) and a high level (∼1500 μatm pCO2). These concentrations span the levels of pCO2 observed and expected in open ocean waters from the year 1750 to 2200 , an ideal food source, at a density of 4 × 104 ml−1 daily to maximize bivalve larval growth and survivorship through metamorphosis (and pCO2  in seawa to 2200  and can −1 in quadruplicate (n = 4) ∼18 h post-fertilization. Twice weekly during experiments, larvae were gently poured onto a 64 μm mesh, and the condition (live or dead) and developmental stage of each larva  was determined visually under a dissecting microscope; every individual live larva was counted at every water change. Larvae from each vessel (n  = 4 per treatment) were removed, counted, observed, and transferred into a new vessel with new filtered seawater, food and antibiotics within a 15 min period. Experiments were terminated after all surviving larvae in all treatments metamorphosed, after ∼3 weeks.For each experiment, larvae were distributed to each 1 l experimental vessel at a concentration of ∼400 ln = 15) from each treatment were stained with a 1:9 dilution of the stock solution and 0.2-μm-filtered seawater. Larvae were exposed to the stain for ∼1.5 h, rinsed with filtered seawater, and digitally photographed with a Roper Scientific Photometrics CoolSNAP ES camera under an epiflorescence microscope to observe lipids. Photographs of each larva were taken and analysed using ImageJ® software for the area of lipid accumulation, the diameter and the area of individuals. Diameters were based on shell lengths. The proportional area of lipid content was estimated as the ratio of lipid area to larval area.At the end of experiments, the relative lipid content of larvae was measured as described by 2 as described above (in the ‘Larvae and treaments’ subsection). These larvae were bubbled with the same tanked gases delivered at the same rates, held in the same vessels within the same water baths, fed the same food, with water changes on the same dates, and displayed survival rates that were similar to and not significantly different from those in the other experimental vessels at the same pCO2 levels. For experiments, ∼200 larvae per treatment were placed into 125 ml polyethylene bottles with 100 ml new filtered seawater; temperature was maintained at 24°C, and the bottles were continuously bubbled to deliver the same CO2 levels that the larvae had been grown in until that point.In order to measure calcification rates during the veliger (day 7) and pediveliger stage (day 16), a separate set of larvae were grown at 250, 380 and 750 μatm pCO2 were assessed using a 45Ca isotope tracer method  for 1 h, after which 10 ml of UltimaGold™ scintillation cocktail was added. Beta activity of the samples was counted on a Perkin Elmer Tri-Carb 1600 liquid scintillation counter, with the discriminator window optimized for 45Ca detection. The weight-specific calcium uptake rate per individual was determined by the following equation:l is radioactivity of live larvae, (dpm)d is the radioactivity of killed larvae, which represents non-biological factors including background, ion-exchange and isotope absorption, Cam is the calcium content of unit medium water (in milligrams per litre), (dpm)m is the radioactivity of unit medium water, t is the length of the incubation (in days) and L is the number of larvae per beaker. This equation is based on the assumption that there is no significant discrimination by larvae for 45Ca and 40Ca uptake ; precise CO2 levels and complete carbonate chemistry from this experiment appear in Table n  = 15) were removed from each treatment beaker (n = 4), poured onto a sieve, and were then macerated using a Pellet Pestle® Motor, heated to 50°C for 15 min, and then frozen to −80°C for at least 90 min. Nucleic acids from pooled groups of larvae per treatment (n = 15) were extracted using a modified cetyl trimethylammonium bromide technique, and quantified using Quant-iT™ RiboGreen RNA® and Quant-iT™ PicoGreen® DNA assay kits (Invitrogen), according to the manufacturer's protocol. RiboGreen® RNA and PicoGreen® DNA are ultra-sensitive fluorescent nucleic acid stains for quantifying RNA and DNA, respectively, in solution. RiboGreen® also binds DNA; therefore, complete DNAse digestion of the sample preceded analysis of RNA. The RNA and DNA concentrations in the extracted samples were determined by measuring fluorescence using an Applied Biosystems 7300 Real-Time PCR system-genetic analyser and compared with a standard curve of nucleic acids.In order to assess RNA:DNA ratios of 2, randomly chosen individuals (n = 6 per vessel) were mounted for scanning electron microscopic imaging as described by © 150B rotary pump.In order to document differences in the size and structure of larval and early oysters exposed to differing levels of CO© 4304) and were impregnated with low-vicosity epoxy (Stuers'© Specifix-20) under vacuum outgassing, a step which did not alter the original shape or size of individuals. After curing, the epoxy mount was progressively ground and polished to the centreline (hinge to shell edge) of the shellfish using silicon carbide sandpapers, followed by successively finer diamond polishing grits , 0.05 μm aluminum oxide suspension and, finally, with colloidal silica. All individuals were cross-sectioned at the same location (hinge to shell edge) across the shell. Measurements of shell thicknesses were made at the precise mid-point between the hinge and valve opening on the upper and lower shell for all individuals. This mount was then attached to a conductive substrate using carbon double-sided tape and coated with ∼4 nm of gold.In order to image the thickness and internal dimensions, cross-sections of shellfish were prepared. Individuals were mounted on glass microscope slides using ultraviolet-curing adhesive coating (LociteScanning electron microscopic images were collected on both types of samples with a Leo (Zeiss) Model # 1550 electron microscope using a high voltage of 20 kV and a Robinson back-scatter detector. All components of individual bivalve shells displayed in Fig. post hoc multiple comparison tests where CO2 levels were the treatment effects. Data that did not meet assumptions of normality and homogeneity were tested using Kruskal–Wallis tests. Statistical analyses were performed with SYSTAT 13© Copyright, 2009, Systat Software, Inc.Percentage data  were arcsine square-root transformed prior to statistical analyses. Differences in survival, size, shell thickness, metamorphosis, RNA:DNA ratios, calcification rates and lipid indexes were assessed using one-way ANOVAs and Tukey's 2 levels have been shown to grow more slowly than conspecifics grown at lower pCO2 levels  generally performed better than those reared at higher and lower CO2 levels . More C. virginica larvae survived at present-day CO2 levels (29 ± 8.1%) compared with the survival at 250 (6.0 ± 3.8%), 750 (19 ± 5.5%) and 1500 μatm CO2 , the differences among the other levels were not statistically significant (P > 0.05).C. virginica larvae grown at present-day CO2 levels , 51 ± 15% of surviving larvae had metamorphosed, while at ∼250, 750 and 1500 μatm, 22 ± 18, 41 ± 12 and 39 ± 0.4% had done so  when grown in present-day CO2 conditions (380 μatm), compared with 250 μatm pCO2 (317 ± 4.7 μm), 750 μatm CO2 (208 ± 7.5 μm) or 1500 μatm pCO2  compared with 250 (6.4 ± 0.76 μm), 750 (5.1 ± 0.53 μm) or 1500 μatm pCO2  compared with the lower (0.3 ± 0.1) and the two higher levels of pCO2  compared with higher  and lower levels of pCO2  were found to have a consistent, cascading negative impact on early life-stage oysters during this study. Individuals experiencing higher (750 or 1500 μatm) levels of pCO2 were smaller, slower to metamorphose and less calcified and had thinner shells in comparison to those at lower pCO2 levels. In an ecosystem setting, these smaller individuals would be more vulnerable to predation (2 (750 or 1500 μatm) also accumulated fewer lipids compared with individuals grown at lower pCO2 levels. Lipids are a key energy store in larvae that are used for growth during early larval stages and are accumulated in later larval stages as an energy store that is used by early juvenile stages  exposed to elevated CO2 display higher metabolic rates, indicating a higher energy demand for homeostasis in these conditions  are indicative of an organism in an active state of transcribing RNA, synthesizing proteins and growth, while lower values are indicative of physiological impairment  the largest amounts of calcium carbonate were likely to accrete on the outer shell of larvae. The significantly lower lipid content of individuals grown at higher pCO2, even after calcification rates were accounted for, further affirmed that these individuals were physiologically challenged and thus unable to devote energy needed for the formation and storage of lipids compared with individuals growing in the presence of lower pCO2 levels  and bay scallops (A. irradians). For example, in the presence of moderate pCO2 concentrations (650 μatm), M. mercenaria and A. irradians larvae exhibited large declines (>50%) in survivorship, while C. virginica did not , the relative decline in their survival is smaller than that of M. mercenaria and A. irradians . Collectively, these findings demonstrate that C. virginica is less sensitive to acidification than some other North Atlantic bivalves and, in fact, performs best at current levels of pCO2 (380 μatm).Ocean acidification research to date has repeatedly demonstrated that there exists substantial variability in the vulnerabilities of ocean animals to high CO2 , 2012 in did not . MoreoveC. virginica is abundant, freshwater tributaries are acidic and, thus, the low-salinity regions of estuaries that naturally have a lower buffering because of low alkalinity also harbour low pH and low calcium carbonate saturation states  may be more tolerant of higher CO2 levels than species that evolved during eras of lower CO2 levels (i.e. M. mercenaria and A. irradians) that seem to perform best at the levels of CO2 that were found prior to the industrial revolution. Still, open questions regarding these species, including the evolution of modern strains, the evolution of their calcification pathways and their ability to adapt to rapidly rising levels of CO2, remain unanswered.Molluscs first appeared during the Cambrian period ∼500 million years ago, while prehistoric oysters are likely to have evolved during the Mesozoic era . Crassossent day . In cont2 and low in pH due metabolic processes. In contrast, other bivalves more sensitive to acidification, such as hard clams and bay scallops, do not approach these densities in the wild. Another bivalve that also exists in high-density beds, the blue mussel (Mytilus edulis), has also shown tolerance to acidification  to settle on, oyster restoration can be a challenge . Lastly, all estuarine bivalves will cope with multiple acidification threats in the coming decades, namely rising levels of atmospheric CO2 (i.e. ocean acidification) coupled with coastal ocean acidification driven by anthropogenically enhanced organic carbon loading (2 levels in some estuaries that are not predicted to occur in the open ocean until the end of this century but that yield lower survival rates of larvae (e.g. ≥1000 μatm; Be it due to its evolutionary history, its biogeography, gametic conditioning, a combination of these factors or factors not considered here, hallenge . Moreoveirginica , 2012. H


Early life adversity increases the risk of mental disorders later in life. Chronic early life stress may alter neurotrophic factor gene expression including those for brain derived neurotrophic factor (BDNF) and glial cell derived neurotrophic factor (GDNF) that are important in neuronal growth, survival, and maintenance. Maternal separation was used in this study to model early life stress. Following unilateral injection of a mild dose of 6-hydroxydopamine (6-OHDA), we measured corticosterone (CORT) in the blood and striatum of stressed and nonstressed rats; we also measured DNA methylation and BDNF and GDNF gene expression in the striatum using real time PCR. In the presence of stress, we found that there was increased corticosterone concentration in both blood and striatal tissue. Further to this, we found higher DNA methylation and decreased neurotrophic factor gene expression. 6-OHDA lesion increased neurotrophic factor gene expression in both stressed and nonstressed rats but this increase was higher in the nonstressed rats. Our results suggest that exposure to early postnatal stress increases corticosterone concentration which leads to increased DNA methylation. This effect results in decreased BDNF and GDNF gene expression in the striatum leading to decreased protection against subsequent insults later in life.  Parkinson's disease (PD) is one of the most prevalent neurodegenerative disorders with age being the major risk factor . ParkinsEarly life stress has been implicated in some of the most prevalent mental disorders and this has led to increasing interest in the effects of stress on neurodegeneration . VictimsProlonged exposure to early life stress increases the baseline circulating glucocorticoid levels; this amongst many of its effects has been associated with compromised neuronal survival , 16. AcuA total of thirty-six rats were obtained from the Biomedical Research Unit of the University of KwaZulu-Natal and kept under standard lab conditions with food and water freely available. On postnatal day 1 (PND 1), the rats were sexed and culled to 6 male pups per litter. Rats were randomly divided into two equal groups. One group was normally reared (NS) and the second group was maternally separated (MS). The maternal separation protocol started on postnatal day 2 and lasted until postnatal day 14. Rats were further subdivided into 4 groups; group 1 was normally reared saline lesioned rats (NS-control); group 2 was normally reared 6-OHDA lesioned rats (NS), group 3 was maternally separated saline rats (MS-control), and group 4 was maternally separated 6-OHDA lesioned rats (MS). All procedures were approved by the Animal Ethics Committee of the University of KwaZulu-Natal .A 3-hour (9 h00 to 12 h00) daily maternal separation protocol was used. Dams were removed from the home cage and placed in a cage with clean bedding. Pups were then removed from the experimental room and placed in a different room to prevent any form of communication between pups and dams. After 3 hours the pups were returned to the animal room and dams were placed back in the home cage. The daily light/dark cycle was from 6 a.m. to 6 p.m. All cages were cleaned once a week. The rats were weaned on postnatal day 21 and left undisturbed until postnatal day 60.μg/4 μL dissolved in 0.2% ascorbic acid; Sigma, St. Louis, MO, USA) infusion unilaterally (0.5 μL/min) using a Hamilton syringe into the right medial forebrain bundle  according to the Paxinos and Watson rat brain atlas [Desipramine , a norepinephrine reuptake blocker which serves to prevent 6-OHDA uptake by noradrenergic neurons, was injected thirty minutes prior to the injection of 6-OHDA. Prior to the injection of 6-OHDA, the animals were anaesthetised with sodium pentobarbital . To aid with respiration during unconsciousness, animals received atropine  before being placed in the stereotaxic apparatus . Animals received an injection of 6-OHDA HCl  which were then centrifuged at 3500 rpm for 10 minutes at 4°C in a refrigerated centrifuge . Plasma was transferred into Eppendorfs and quickly frozen in liquid nitrogen. Immediately after decapitation, the brain was removed from the skull and placed in frozen 0.9% saline slush before the striatum was dissected out and quickly frozen in liquid nitrogen. The frozen tissue was stored in a biofreezer at −80°C where it remained until the day of analysis.μL) before being used. The sonicated sample, standards and controls (20 μL each), was pipetted into respective well plates. Enzyme conjugate (200 μL) was added into each well followed by incubation (60 minutes). After the incubation period, the wells were washed after which Substrate Solution (100 μL) was added into each well. After 15-minute incubation, Stop Solution (50 μL) was added to each well to stop the reaction. Optical density (OD) was measured at 450 nm within 10 minutes.Corticosterone concentration was measured in blood and striatal tissue using rat corticosterone ELISA kit . Striatal brain tissue was homogenised in PBS . The protocol consisted of extraction and quantification. Extraction continued overnight and quantification was performed the following day.2O (95 μL), 2x digestion buffer (95 μL), and proteinase K (10 μL) was added to tissue containing microcentrifuge tubes. The solution was mixed and incubated for 3 hours at 55°C. After incubation, genomic lysis buffer (700 μL) was added to each tube and mixed by vortexing. The mixture was centrifuged at 10,000 ×g for 1 minute after which the supernatant was transferred to a zymo-spin IIC column in collecting tubes and centrifuged at 10,000 ×g for 1 minute. DNA prewash buffer (200 μL) was added to the spin column in a new collecting tube and centrifuged for 1 minute. g-DNA wash buffer (400 μL) was added to the spin column and then centrifuged for 1 minute. The spin column was then transferred to a clean microcentrifuge tube; DNA elution buffer (200 μL) was added to the spin column followed by 5-minute incubation at room temperature. The tubes were then centrifuged for 30 seconds at 5000 ×g after which they were stored at −20°C.Frozen striatal tissue was prepared using ZR Genomic DNA-Tissue Mini Prep  as follows: a solution consisting of HμL) was added to 5-mC coating buffer (95 μL) in a PCR tube. Standards and negative and positive controls were also prepared . These were then denatured at 98°C for 5 minutes in a thermal cycler. The denatured DNA was immediately transferred to ice for 10 minutes after which it was transferred to the plate, covered with foil, and incubated at 37°C for 1 hour. Following the incubation, the buffer was discarded and each well was washed 3 times with 5-mC ELISA buffer (200 μL). ELISA buffer (200 μL) was added to each well; the plate was covered and incubated at 37°C for 30 minutes, after which the buffer was discarded. Antibody mix (100 μL) was then added to each well. The plate was covered with foil and incubated at 37°C for 1 hour. For color development, the antibody mix was discarded and each well washed 3 times with 5-mC ELISA buffer (200 μL). HRP developer (100 μL) was added to each well and the plate placed at room temperature for 10–60 minutes to allow for color development. Absorbance was measured at 405 and 450 nm using an ELISA plate reader.The prepared DNA (5 μg) was reverse-transcribed into cDNA using a cDNA synthesis kit . cDNA was amplified by real time PCR (Lightcycler 96). The primers (β-actin), followed by final extension at 72°C for 8 minutes.RNA was extracted from the tissue using an All ZR RNA MiniPrep Kit . Total RNA . Nonparametric tests were used followed by Mann-Whitney∗(NS-control versus MS-control); #; #; #; #, #. We found a higher % 5-mC in the striatum of rats that were exposed to maternal separation stress compared to nonstressed rats. It has been hypothesised that maternal separation leads to behavioural and neuroendocrine changes and may also alter the DNA methylation status . Chronicμg/4 μL dose producing a mild lesion [Induction of the 6-OHDA lesion did not have an effect in % 5-mC as there were no differences between the nonstressed control and the nonstressed lesioned rats and also no significant changes in the % 5-mC in the maternally separated control rats compared to the maternally separated lesioned rats. This increase seen in the stressed rats suggests that prolonged early maternal stress negatively affects the proper development of the neural circuits altering gene expression, thus facilitating epigenetic changes that will result in modification of genes . Our resd lesion . Parkinsd lesion . The 6-Od lesion  and hencWhen we measured the expression of neurotrophic factor genes, we found a lower concentration of BDNF and GDNF gene expression in the stressed rats compared to the normally reared rats. The current result suggests that early life adversity alone may cause epigenetic changes that weaken the brain's ability to protect itself against an injury or insult. This is further supported by the lower neurotrophic factor gene expression in the stressed rats that were injected with 6-OHDA. In the presence of 6-OHDA, there was an increase in the neurotrophic factor gene expression on both the nonstressed and stressed rats in response to tissue injury. This increase was, however, much higher in the normally reared rats when compared to the stressed rats. Our results show that stressed rats were not as responsive to the injury as the nonstressed rats. This may be the reason we see greater dopamine degeneration in stressed animals following 6-OHDA injection , 34. TheMaternal separation is a form of early life stress that has been shown to alter the developing neuronal circuitry. This has been previously linked to the development of neurological disorders.In agreement with previous studies, our findings have shown that early life stress in the form of maternal separation increases baseline circulating corticosterone concentration leading to the alteration in gene expression. These epigenetic changes result in an altered expression of BDNF and GDNF genes which may lead to a decrease in the concentration of these neurotrophic factors. This results in the brain being more vulnerable to insults leading to exacerbated neurodegeneration.