Relative sea level rise (RSLR) largely regulates the CAR. The tidal wetland CAR is projected to increase in this century and continue their C sequestration capacity in all climate change scenarios, suggesting a strong resilience to sea level rise. These results serve as a baseline assessment of C accumulation in tidal wetlands of US, and indicate a significant C sink throughout this century.Coastal wetlands are large reservoirs of soil carbon (C). However, the annual C accumulation rates contributing to the C storage in these systems have yet to be spatially estimated on a large scale. We synthesized C accumulation rate (CAR) in tidal wetlands of the conterminous United States (US), upscaled the CAR to national scale, and predicted trends based on climate change scenarios. Here, we show that the mean CAR is 161.8 ± 6 g Cm It remains challenging to estimate carbon accumulation rates in tidal wetlands on a scale as large as the conterminous US. Here, the authors find that mean C accumulation rates vary greatly among watershed regions but not among vegetation types, and that tidal wetlands’ C sequestration capability will remain or increase by 2100, suggesting a resilience to sea level rise. Despite only covering 2% of the earth’s ocean surface, global tidal wetlands have been roughly estimated to bury ~ 116 Tg C yr−1, which accounts for over 50% of annual C burial in the ocean3. The C stocks and fluxes in these intertidal environments are collectively regarded as coastal wetland blue carbon1.Tidal wetlands, including tidal marshes and mangroves, contain long-term soil organic carbon (C) of which continuously sequester atmospheric carbon dioxide at rates 10–100s times higher than terrestrial forests1. Thus, the rate of sediment C sequestration can be maintained as long as the soil accretion continues to keep pace with sea level rise. In terrestrial ecosystems, although fast C restoration rates were recorded in vegetations and/or soils after disturbance5, these rates were maintained only on a decadal scale5, and would reach a relative saturation point after restorations when the net C sequestration rate approximates to zero owing to increased soil and vegetation respiration. Therefore, the longevity of tidal C sinks has a greater potential than terrestrial C sinks in mitigating climate change over longer periods. There is an increasing global interest in coastal wetlands as targets for greenhouse gas emission offset projects through the preservation and restoration of these ecosystems to increase future C sequestration6.Soils in these blue C ecosystems, unlike terrestrial ecosystems, do not become saturated with C as they accrete vertically under the impact of rising sea levels10. In a New England salt marsh, Redfield and Rubin11 reported well-maintained soil elevation equilibrium with sea level for the previous 4000 yrs. Morris et al.7 developed a model to predict the response of coastal wetlands to rising sea level, and reported that limiting rate of RSLR on the southeast coast of US was predicted to be 12 mm yr−1, which is 3.5 times greater than the current long-term rate of RSLR, indicating that SAR in the coastal wetlands of this region could keep pace with current RSLR. In comparison with SAR, the C density usually varied substantially across different vegetation types and regions as revealed in the 2013 compilation by the International Panel on Climate Change (IPCC)12. Although some studies have reported a negative relationship between soil C density and mean annual temperature13, this relationship is very weak, and studies have yet to explain the variability in carbon density across different regions. Higher decomposition rates of soil organic matter usually accompany higher temperatures. However, higher temperatures also enhance plant productivity, which would partially compensate the loss of C through increased decomposition14. Therefore, a more thorough understanding of the drivers of tidal wetlands C sequestration is highly needed.Rates of C sequestration in tidal wetlands depend upon their vertical sediment accretion rate (SAR) and soil C density. In healthy tidal wetlands, SAR generally keeps pace with relative sea level rise (RSLR) by the accumulation of mineral and organic sediment218. Hinson et al.16 estimated that there was 1153–1359 Tg of SOC stored in the upper 0–100 cm of soils in 24945.9 km2 tidal wetlands across the conterminous United States. This value was over 10% of total the C stocks in top 0–120 cms soils of all US wetlands estimated by Nahlik and Fennessy17, whereas tidal wetlands only accounted for 6.5% of total area of all wetlands in the conterminous United States , highlighting the importance of tidal wetlands in storing carbon. Moreover, this value may still greatly underestimate the soil C stocks in tidal wetlands as their soil profiles are known to reach six to 13 m in depth, and their C density has generally been found to be consistent with depth19, indicating their disproportional contribution to the total wetland C storage when the entire soil profile is considered.The USA has vast tracts of tidal wetlands, with a total area in the range from 22,000 to 26,000 km20, no study has provided a detailed spatial distribution of their C sequestration or C accumulation rates on a national scale. Hinson et al.16 estimated the C sequestration rate to be ~ 1.5 Tg C yr−1 in the conterminous United States tidal wetlands. This estimation was obtained by simply assuming a C burial rate of 60 g m−2 yr−1 and the C density to be 0.03 g cm−3 for all tidal wetlands. However, these estimates may be highly underestimated21. Using 154 sites across the globe, Chmura et al.13 found that the average soil C density is 0.055 g cm−3 and 0.039 g cm−3 in mangrove and salt marsh, respectively. According to the US Inventory of Greenhouse Gas Emissions and Sinks, US tidal wetlands sequestered 3.3 Tg C yr−1 during the period from 2005 to 201620. This value was derived from a synthesis of peer-reviewed literature, but the details in calculating this value were not provided. Therefore, a spatially explicit database that details tidal wetland C sequestration rates is needed for Tier 2 estimation of the conterminous United States. Furthermore, the balance of controlling factors and their relative contributions to C sequestration is not well known in the tidal wetlands. Identifying the controlling factors of C accumulation dynamics is critical for understanding the fate of the C buried by these wetlands under future climate change and human activities.Although the total C stocks of these tidal wetlands across the conterminous United States have been estimated by several independent studiesIn this study, we aim to estimate the C accumulation rate in different regions in the conterminous United States from compiled data, evaluate the factors controlling the spatial patterns of sediment accretion and C accumulation, and predict the future C fluxes in these tidal wetlands. We show that tidal wetlands would continue their C sequestration capacity in all representative concentration pathways scenarios even under the most-restricted lateral accommodation space availability in the conterminous United States, which suggests a strong resilience to sea level rise.−2 yr−1  in the conterminous United States tidal wetland were estimated to be 161.8 ± 6 g C m−3 to 0.045 g C cm−3, with the highest rate at the Mid Atlantic region, and the lowest at the California region. We collected 343 unique measurements of soil accretion rate (SAR) across the conterminous United States. A comparison with the local rate of RSLR indicated that 130 of 343 sites were submerging, whereas the remaining sites have higher SAR than the local RSLR rate  was similar to the regional RSLR , which was significantly higher than those in other regions except for the Texas-Gulf , whereas accounting for ~ 46 % of the annual C sequestration . More than half of annual US tidal wetland C sequestration occurred in the Gulf-Bay (Lower Mississippi and Texas-Gulf: 2.70 Tg yr−1), followed by East Coast  with 1.96 Tg yr−1, with the lowest in the West Coast (0.07 Tg yr−11).The lower Mississippi region had 32% of the tidal wetlands area in the conterminous United States 8193 km93 km2, w−2 yr−1), which was significantly higher than the values in CA, CT, FL, GA, MA, ME, NC, NJ, VA, and WA  among the coastal states. The lowest average CAR (62 ± 7.8 g C m−2 yr−1) was found in GA. LA also had the largest tidal wetland area among these states, up to 9089 km2. Combined with its high CAR  among all the vegetation types, and the value was only approximately half of the rates found in the other three vegetation types (Table p < 0.05).The CAR was the highest in brackish, followed by tidal freshwater wetlands, and the lowest at mangroves , but had no significant relationship with Prcp. The CAR decreased with increasing Latitude  in 2100 if their lateral accommodation space is not restricted by human activities to population density higher than 300 peoples/km2 , the tidal wetlands still sequester 4.32, 4.29, and 4.13 Tg C yr−1 under RCP 2.6, RCP 4.5, and RCP 8.5 scenarios, respectively  was much lower than the global mean value (244 g C m−2 yr−1) reported by Ouyang and Lee24, but similar to the rate (151 g C m−2 yr−1) reported by Duarte et al.2. This difference can be explained by the latitude range: both of this study and the one by Duarte et al.2 has similar latitudinal ranges (25–50°N), whereas the global averages estimated by Ouyang and Lee24 included data from other regions, like Asia-Pacific, Arctic, and Australasia. In mangroves, Breithaupt et al.21 reported the geometric mean of the global CAR database to be 163.3 g C m−2 yr−1, which is similar to that in this study (151.5 ± 16 g C m−2 yr−1).Compared with previous estimations, the rates in this study show both differences and common features. In salt marsh, our average CAR . DeLaune and White25 obtained this value by multiplying a 300 g C m−2 yr−1 C burial rate with the coastal wetlands area in 1990, which was 9889 km2. Although their C burial rate is similar to what we report here, the total wetland area is over 10% less in our study. In this study, we used the most recent NWI data set (2017), which indicated that the tidal wetlands in LA had shrunk to 9086 km2.Lousiana (LA) had the most extensive tidal wetlands and the highest C accumulation amount among all the coastal states. DeLaune and White24 estimated that there was 1.39 Tg C yr−1, 0.36 Tg C yr−1, and 2.52 Tg C yr−1 C accumulated in salt marshes of East Coast, West Coast, and Gulf-Bay, respectively. They also reported that the highest CAR rates occurred in the Gulf-Bay regions, especially the LA salt marshes. This spatial pattern is in agreement with our results that the Lower Mississippi region has the highest average CAR (271 ± 18 g C m−2 yr−1). This value was also similar to 300 g C m−2 yr−1 CAR reported by DeLaune and White25 for LA coastal wetlands. However, the big difference between this study and Ouyang and Lee24 is the areal data for the West Coast. Ouyang and Lee24 reported 2685 km2 tidal marsh, which is over four times larger than the area (640 km2) in this study. Our areal data are similar to 567.5 km2 tidal wetlands in West Coast reported by Hinson et al.16 who also extract the tidal wetland area from US wetland inventory dataset. Ouyang and Lee24 did not provide details on how they obtained this data, but from their Fig. 2 should be for the Northeast Pacific, which includes the tidal wetlands in the Pacific coast, Alaska, Mexico, and Canada. CEC18 also reported the Northeast Pacific coastal area to have over 3423 km2 tidal wetlands, with ~ 80% located in Mexico as mangroves and tidal shrub. It thus is highly possible that Ouyang and Lee24 largely overestimated the tidal marsh area in the West Coast of the conterminous United States. Furthermore, we had 47 sites in the West Coast which was nearly six times higher than the number reported by Ouyang and Lee24. Therefore, our estimation based on these detailed soil CAR sites and NWI tidal wetlands database is more site-specific than previous reports.To our knowledge, there are no detailed reports on the national-wide tidal wetland C sequestration rate in the conterminous United States prior to the present study. However, some regional estimates of CAR were available for comparison. From the 104 measurements of CAR in salt marsh in the conterminous United States, Ouyang and Lee20 estimated that 3.3 Tg yr−1 C had accumulated annually in the top 1 m sediments of 29,000 km2 coastal wetlands in the conterminous United States since 1996. However, there are no details on how the value is calculated. Owing to the significant difference in regional CAR, simply upscaling one single average C accumulation rate to national and/or regional levels would cause large uncertainties in the total C accumulation. For example, the lower Mississippi region has 8193 km2 tidal wetlands with the average CAR at 271.9 g C m−2 yr−1. There will be 40% underestimation if we use the national CAR average rate 161.8 g C m−2 yr−1 for the regional upscaling. Similarly, upscaling according to mean values on the vegetation types would also underestimate the national C sequestration rate. In this study, the average CAR for tidal freshwater wetlands, brackish, salt marsh, and mangroves are 166.2, 179.7,154.3, and 151.5 g C m−2 yr−1, respectively. By multiplying these rates with their corresponding areas, there is 4.19 Tg C accumulated annually in the conterminous United States, which is still 0.4 Tg C lower than the data estimated based on the complete NWI tidal wetlands sum (4.59 Tg C yr−1).Another advantage to our compiled soil C accumulation data is that we upscaled the site-specific CAR to the spatial area with NWI tidal wetland database. This method ensures that records from regions with high or low density of observations are not unduly weighed in the upscaling process. The EPA−2 yr−1) is much lower than the global mean value (210 ± 20 g C m−2 yr−1)13, it is still nearly three times higher than the estimation (60 g C m−2 yr−1) by Hinson et al.16 for all tidal wetlands in the conterminous United States. Hinson et al.16 got 60 g C m−2 yr−1 CAR by assuming that the SAR for US coastal wetlands to be the same to sea level rise rate (2 mm yr−1) and C density to be 0.03 g cm−3. As a result of this extrapolation, Hinson et al.16 estimated that there was only ~1.5 Tg C sequestrated by tidal wetlands annually. Although their estimation of sea level rise rate is reasonable, the SAR was reported to keep pace with RSLR rather than sea level rise rate10, because RSLR is a combination of sea level rise and vertical land movements26. In Lower Mississippi region, for example, land subsidence rate is 3–4 times faster than sea level rise rate , and RSLR reached to 8.82 mm yr−1. In this study, the average SAR rate ranged from 3.2 mm yr−1 (Pacific Northwest) to 8.9 mm yr−1 (Lower Mississippi), both of these two values were much higher than the SAR rate assumed by Hinson et al.16. Moreover, as mentioned above, simple upscaling using average national data would greatly underestimate the C sequestration amount in regions with high CAR, like the Lower Mississippi, which has large areal tidal wetlands.Although our average CAR  than salt marsh (0.035 ± 0.001 g cm−3). Chmura et al.13 also reported that the average soil carbon density in mangrove (0.055 ± 0.004 g cm−3) was much higher than that in salt marsh (0.039 ± 0.003 g cm−3) across the global data set. Tidal freshwater wetlands contained the highest SAR but the lowest C density, whereas mangroves had the highest C density but lower SAR , RSLR is shown to have a significant effect on organic sedimentation rather than on mineral sedimentation, indicating that plant originated organic sedimentation feedbacks to RSLR drives the resilience of tidal wetland vertical accretion to sea level rise. This result was also in agreement with Morris et al.28 that organic sedimentation contributes ~60% to vertical accretion in the East Coast estuaries.The resilience of tidal wetlands to sea level rise depends on its vertical accretion rate and/or potential horizontal migration to upland. With ongoing climate change, the CAR in tidal wetlands can be either maintained or even increased as long as SAR keeps pace with RSLR34, and the net changes in tidal wetland area would be minimal or even increase. However, human activities greatly affect the landward migration of tidal wetlands in costal regions. Schuerch et al.23 predicted global tidal wetland area change based on an integrated modeling approach, which considered both the ability of coastal wetlands to build up vertically and laterally by sediment accretion and the accommodation space, respectively. They found that global tidal wetland would increase ~60% of the current area if these wetlands have sufficient accommodation space, but could lose up to 30% of their aerial extent assuming no further accommodation space in addition to current levels23.Horizontal migration also helps tidal wetlands to adapt and survive under sea level rise. Wetland losses at the seaward margin could be offset by the migration to highland23) and CAR response to future RSLR. Under the most-restricted accommodation space status , the conterminous United States tidal wetlands area in 2100 will lose up to 25% of their aerial extent in 2100, but the net CAR loss would be <10 %. Similarly, the tidal wetlands net annual C gains would be doubled but the net area only increased by <50% under the upper estimates for current accommodation space in 2100 . LOI measurement of mangrove and tidal freshwater marsh soils were transformed into organic C content by dividing a factor of 1.72428. The model assumes that the bulk volume of sediment is equal to the sum of self-packing volumes of organic and mineral components or [BD = 1/[LOI/k1 + (1 − LOI)/k2], where k1 and k2 are the self-packing densities of the pure organic and inorganic components, respectively. The values of k1 and k2 were estimated to be 0.085 ± 0.0007 g cm−3 and 1.99 ± 0.028 g cm−3, respectively28.BD was also not reported in some sites. The missing BD was calculated based on a mixing model which describes the BD as a function of LOI in intertidal wetland sediments137Cs and 210Pb dating methods were employed in 317 sites to determine decadal rates of vertical accretion, and 24 sites measured sub-decadal and decadal SAR based on the surface elevation table methods. Only one study used 14C dating method to rebuild centuries to thousands of years accretion rates11. The 14C dating method usually has a lower SAR than the method using 137Cs and 210Pb39. To avoid statistical skew by dating methods, this study was not included in the final CAR calculation. Where reports made available both SAR and C density, the CAR was calculated. Some studies have reported the SAR and C density or C content for multiple layers, reflecting their changes over time. For these studies, we averaged their C density and SAR over the up 30 cm soils, which recorded the most recent C accumulation (<100 yrs).Most of the collected studies reported the vertical SAR in recent decades, which allowed us to calculate the carbon accumulation rates (CAR). The vertical SAR represented average SARs from decades to centuries, depending on the different dating methods. The 40. RSLR data were collected from the Permanent Service for Mean Sea Level database41. Annual tide-gauge data were smoothed by fitting a temporal linear model to calculate the RSLR. To avoid the recorded RSLR rate being dominated by decadal variability in different tidal gauges43, we standardized the long-term tidal gauges data set and only reported the most recent 60 yrs RSLR , mean annual precipitation (Prcp), the RSLR, and salinity were also collected. Tair and Prcp for each site were acquired from National Centers for Environmental Prediction atmospheric reanalysisAll the reported coastal tidal wetlands were categorized into four groups according to their salinity and dominant vegetation types. Tidal freshwater wetlands have salinity in the range from 0 to 0.5‰, brackish is the tidal marsh whose salinity ranged from 0.5 to 18‰, and salt marshes have the salinity over 18‰. In salt marsh, many studies also reported the difference between high marsh and low marsh, o to their distinguished elevation distribution.https://www.fws.gov/wetlands/). The NWI uses a classification system for aquatic habitats, including systems, subsystems, and classes. The wetlands extracted from the NWI for this study contain not only ‘blue carbon’ in the IPCC Wetlands Supplement44, but also tidal freshwater wetlands. Based on their locations and NWI classifications, we extracted 325,255 tidal wetland polygons from the NWI database and classified them into four types: tidal freshwater wetlands, brackish, salt marsh, and mangroves. The detailed classification codes of the four vegetations were listed in Supplementary Table https://www.usgs.gov/core-science-systems/ngp/national-hydrography/watershed-boundary-dataset) to each tidal wetland. CAR, SAR, C density, Tair, Prcp, and RSLR, were also assigned to these tidal wetlands.Locations and vegetation types of tidal wetlands were extracted from the National Wetland Inventory (NWI) data set . We thus assumed that C accumulation at one sampling site might have the highest similarity to that at the nearby sites. Spatial interpolation methods have been used in this study to calculate the CAR of each of the tidal wetlands in the conterminous United States: the CAR of each tidal wetland polygon  was estimated based on compiled sites within the radius of 100 km. The 95% confidence intervals (CI) of each tidal wetland polygon was also estimated by assuming that nearby available CAR data sites could represent the CAR values for the wetland. There were still many wetlands  that do not have any or only one nearby available value. For these wetlands, we used the regional mean and CI values to estimate their CAR and CI. The state level and regional C sequestration amounts were summarized based on the data for each tidal wetland. The CI of summed values was propagated based on the below equations (E1 & E2)The CAR, SAR, C density, organic and mineral sedimentation data were grouped by vegetation types, HUC2 watershed regions, and states. We separated all the US conterminous data into seven watershed regions: New England, Mid Atlantic region, South Atlantic and Gulf, Lower Mississippi, Texas-Gulf, California, and Pacific-North Fig. . For salOne-way analysis of variance (ANOVA) was used to detect the difference in above variables among vegetations and watershed regions. The CAR changes among all coastal States were also analyzed with one-way ANOVA. Turkey-HSD was then conducted for multiple comparisons. The ANOVA was performed by using the aov function in the base package of R version 3.3.2 .χ2 test. The Pearson correlation and partial correlation was performed using R version 3.3.2. Pathway analyses were conducted using the Amos 21.0 .Correlation analysis and pathway analysis were conducted to investigate the relationship between tidal wetland CAR and climate and environmental variables. Partial correlation was conducted for the analysis among CAR, SAR, and C density. The pathway analysis was implemented using the maximum likelihood estimation method and was fitted with the 22 in IPCC Representative Concentration Pathway (RCP) scenarios.To select the most relevant predictors of CAR, we used stepwise algorithm based on AIC selection with linear mixed models. The independent variable was CAR, whereas the predictors were HUC2 watershed regions, vegetation types, MAT, MAP, RSLR, Longitude, Latitude. That is, CAR ~ HUC2 + Vegetation + MAT + MAP + RSLR + Longitude + Latitude, with the source of reference as random factor. Only RSLR was included in the most parsimonious final model. We thus used the mixed linear relationship between CAR and RSLR to predict CAR with projected RSLR data23 under different IPCC scenarios and population density threshold. In brief, Schuerch et al.23 predicted global tidal wetland area change based on 12,148 coastal line segments from the Dynamic Interactive Vulnerability Assessment (DIVA) modeling framework46 by a integrated modeling approach, which considered both the ability of coastal wetlands to build up vertically and laterally by sediment accretion and the accommodation space, respectively. They set four population density thresholds  for lateral accommodation space availability, which means the segments have higher population density than the thresholds would have no lateral accommodation space for the tidal wetland. In this study, we extract the conterminous United States tidal wetland area percentage changes from the global 12,148 coastal line segments under all population thresholds in RCP 2.6, RCP 4.5, and RCP 8.0 scenarios.Prediction of the conterminous United States tidal wetland C accumulation: The spatial and temporal prediction of the conterminous United States tidal wetlands C accumulation was based on the projected tidal wetland area changes by Schuerch et al.22 at decadal intervals for locations of each coastal wetland segment under RCP 2.6, RCP 4.5, and RCP 8.5 trajectories. Site-to-site differences in the RSLR projections22 originate from varying non-climatic background uplift or subsidence, oceanographic effects, and spatially variable responses of the geoid and the lithosphere to shrinking land ice. The projected CAR was thus calculated based on RSLR differences between current (the 2010s) values and future values. However, CAR generally reached a maximum rate if SAR cannot keep pace with RSLR29. Previous study predicted a critical RSLR rate of about 10 mm yr−1 for many typical salt marshes in the US and Europe8. Below the critical RSLR rate, tidal wetlands are stable ecosystem, and CAR will keep increase with higher RSLR till the critical rate reached. However, this 10 mm yr−1 critical rate may lead to a conservative estimation of CAR in response to future RSLR in many US coastal wetlands as Morris et al.7 predicted that the critical rate of RSLR on the southeast coastal marshes of US was 12 mm yr−1. The projected coastal wetland C accumulation amount till 2100 was calculated based on projected future CAR and coastal wetland area changes for each coastline segment.To estimate changes in future CAR under projected IPCC scenarios by 2100, we applied the mixed linear model predicted CAR by RSLR. We extracted the conterminous United States future RSLR mean values from Kopp et al.Further information on research design is available in the Peer Review FileSupplementary InformationReporting Summary


Escherichia coli and Saccharomyces cerevisiae. The progress using these different approaches is discussed.Glucosinolates (GLSs) are sulfur‐rich, amino acid‐derived defense compounds characteristic of the Brassicales order. In the past, GLSs were mostly known as anti‐nutritional factors in fodder, biopesticides in agriculture, and flavors in condiments such as mustard. However, in recent times, GLSs have received increased attention as promoters of human health. This has spurred intensive research towards generating rich sources of health‐promoting GLSs. We provide a comprehensive overview of the biotechnological approaches applied to reach this goal. This includes optimization of GLS production and composition in native, GLS‐producing plants, including hairy root and cell cultures thereof, as well as synthetic biology approaches in heterologous hosts, such as tobacco and the microbial organisms  Barbara Ann HalkierEdited by: Uwe Sonnewald, Friedrich‐Alexander University, GermanyGlucosinolates (GLSs) are important defense compounds present in the Brassicales order, including the brassicaceous vegetables, for example, cabbages, radishes and broccoli , from which oil‐rich seeds are used for oil production.The goitrogenic effect upon intake of high GLS content makes the otherwise protein‐rich seed cake of oilseed crops unsuited as animal feed , it becomes ever more desirable to increase the intake of GLSs. Towards achieving high‐level sources of GLSs multiple approaches have been applied, including classical breeding, transgenic approaches, hairy root and plant cell cultures, as well as microbial production with synthetic biology approaches. Previous reviews on this topic focused on individual biotechnological approaches. In this review, we include all approaches and compare the production levels achieved.S‐glycosidic bond to the C‐atom in a sulfated oxime. The GLS core structure is linked to a side chain derived from the precursor amino acid . Subsequently, the molecule can either be transaminated by a BCAT and enter the GLS core structure pathway or proceed through another round of chain elongation (only methionine).A comprehensive review on the elucidation of the GLS biosynthetic pathways and genes involved is provided by Sønderby et al. . BrieflyS‐transferases (GSTs). Cleavage by γ‐glutamate peptidases, GGPs, forms S‐alkyl‐thiohydroximates, which are subsequently cleaved by C‐S lyases to produce thiohydroximates that are S‐glucosylated by glucosyltransferases, UGTs of the 74 family, to form desulfoglucosinolates. Finally, desulfoglucosinolates are sulfated by sulfotransferases, SOTs, to generate GLSs  was crossed with a wild variant (B. villosa) that naturally has higher levels of 4MSB, and a 10‐fold increase in total GLS content in the F1 generation was obtained. Surprisingly, the extracts of the new variant showed a 100‐fold increase in in vitro assays detecting induction of phase II detoxification enzymes in cell cultures. The exceptionally high induction was due to a more efficient conversion of GLSs to ITCs as opposed to other breakdown products  and upregulating the health‐promoting 4MSB in three B. oleracea crops; broccoli, cauliflower, and collard greens  and its ITC , CYP79A1 (from Sorghum bicolor), and CYP79D2 (from cassava Manihot esculenta) into A. thaliana to improve plant defense. Expression of CYP79D2 resulted in the accumulation of isopropyl and methylpropyl GLSs with an enhanced resistance against the bacterial soft rot pathogen Erwinia carotovora. Expression of CYP79A1, or overexpression of the endogenous CYP79A2, resulted in the accumulation of p‐hydroxybenzyl GLS (pOHB) and BGLS, respectively, with increased resistance against the bacterial pathogen Pseudomonas syringae. Surprisingly, increased accumulation of the aromatic GLSs showed enhanced susceptibility to the fungus Alternaria brassicicola  and in the thio‐glucose moiety with the S originating from cysteine in glutathione. Methionine‐derived GLSs may have a third sulfur atom in their structures dependent of the side chain modifications. Falk et al.  reviewedIn summary, classical breeding as well as transgenic approaches have been successful in modifying GLS content in brassicaceous plants for increasing both health benefits and resistance to pathogen attacks. Noticeably, simple sulfate feeding yielded the highest increase in GLSs. The approaches differ in their ability to enable global increase in GLSs, or enrichment of a specific GLS, so the choice of strategy will depend on the purpose, for example, pest resistance or nutritional value.Plant cell cultures are a popular choice for production of specialized metabolites. They have the advantage of being plant tissue cultivated in liquid cultures. Similar to microbial cultures, plant cell cultures allow for several optimization strategies, such as precursor feeding and media and cultivation modifications. In addition, strain improvement through screening or engineering as well as elicitors have been successfully used to increase production . Overexpression of the MYB28 transcription factor, a key regulator of aliphatic GLSs, in A. thaliana cell culture resulted in an increase to approximately 2.3 μmol/g fresh weight (FW), which is still roughly 1.5‐fold lower than in the rosette of a wild‐type plant  produced 18 μg/g FW aromatic GLSs , which produced 44 μmol/g DW BGLS (Wielanek and Urbanek Induction of GLS production in cell cultures by treatment with 50 μM methyl jasmonate (MeJA) for 24 h increased the GLS production with a higher induction of indolic GLSs compared to aliphatic GLSs  than in leaf tissue (18.69 μmol/g DW) and roots (4.70 μmol/g DW)  and turnip (B. rapa ssp. rapa)  contained only four indolic GLSs: indolyl‐3‐methyl GLS (I3M), 4‐hydroxy‐I3M (4OH‐I3M), 4‐methoxy‐I3M (4MO‐I3M) and N‐methoxy‐I3M (NMO‐I3M) at a total GLS concentration of 22.24 μmol/g DW when grown in full B5 media , hairy roots produced approximately 85 μmol/g DW (Wielanek and Urbanek As for the cell cultures (see above), several cress species have been tested as a GLS source in hairy roots. With the BGLS‐producing Indian cress  and land cress (Barbarea verna) that both have particularly high levels of 2PE, and from mountain rock cress (Arabis caucasica) that produces aliphatic GLSs  were transiently expressed in N. benthamiana. Two metabolic bottlenecks related to the addition of reduced and oxidized sulfur, respectively, were identified.In the last decade, much research on establishment of GLS biosynthetic pathways in the non‐brassicaceous tobacco plant was reported. The first example of A. thaliana APK2 kinase, active in the PAPS generation cycle, resulted in efficient conversion of phenylalanine to BGLS without accumulation of intermediates. When BGLS production was stably engineered into Nicotiana tabacum  − a specialist that uses GLSs as oviposition stimuli − laid its eggs on the BGLS‐producing tobacco, and the eggs did not hatch (unpubl. results). This provided proof‐of‐concept for genetically modified dead‐end trap crops.First, accumulation of a GSH conjugate of the product of CYP83B1 resulted in the discovery of the missing enzyme γ‐glutamyl peptidase 1, GGP1  were co‐infiltrated with indolic GLS biosynthetic genes, I3M was converted to 4OH‐I3M by CYP81F1, CYP81F2, and CYP81F3, but not CYP81F4, and all four CYP81Fs catalyzed I3M to 1OH‐I3M. However, GLS profiles of individual cyp81f mutants in A. thaliana showed that NMO‐I3M levels were reduced substantially in the cyp81f4 mutant without the other CYP81Fs being able to compensate, which suggests that CYP81F4 is mainly responsible for hydroxylating at the C1‐position.The pathway for indolic GLSs was engineered into N. benthamiana, demonstrating the feasibility of engineering chain‐elongated GLSs leucine and dihomo‐(iso)leucine , 4‐methylthiobutyl (4MTB), and 4MSB GLS were produced, as well as the chain‐elongated leucine‐ or isoleucine‐derived GLSs not found in the native N. benthamiana resulted in a 9‐fold increase, to approx. 430 nmol/g FW, using a different combination of genes for methionine chain elongation  of the aromatic core structure pathway from A. thaliana along with a myrosinase from the aphid Brevicoryne brassicae and MetC from E. coli to replace A. thaliana C‐S lyase (SUR1). The P450 enzymes were N‐terminally modified as previously described , B. rapa (BCAT3 and CYP83B1), B. oleracea (MAM1 and CYP79F1) and a fungus Neurospora crassa (SUR1). GGP1 and GST genes were not included and the P450 enzymes were modified by fusing them together with ATR2. Expression of the 13 genes resulted in detectable production of 4MSB (Yang et al. S. cerevisiae.Recently, the problem of unwanted byproducts was seemingly circumvented by choosing in vivo and only one could quantify this production. Generally, the threshold for production levels considered financially sustainable is in the grams‐per‐liter range. By this standard, the GLSs produced in microbial hosts are approximately 1,000‐fold too low for large‐scale production. This problem can appear daunting. However, many strategies for optimization are still open for investigation, for example, multivariate optimization and directed evolution approaches (Yadav et al. Microbial engineering of GLSs is still early research and only two studies have successfully produced GLSs in vivo. In a mouse study, a normal healthy diet with GLSs from brassicaceous vegetables was supplemented with an E. coli strain that produces a myrosinase and is engineered to bind specifically to colon cancer cells. The ITCs release was thereby focused close to a tumor. The authors reported 95% inhibition of cancer cell growth in vitro and reduced tumors in vivo of mice fed with the engineered E. coli and brassicaceous vegetables.As an alternative approach to microbial engineering for the production of GLSs or ITCs for human health, Ho et al.  optimizeAs a means to enrich average intake of health‐promoting GLSs, high levels of 4MSB were successfully obtained in the Beneforte™ broccoli using a classical breeding approach. Other approaches have focused on identification of suitable hosts for high GLS production. GLS engineering in heterologous hosts poses several challenges. The special sulfur chemistry associated with GLSs and for which the cruciferous hosts have learnt to cope, gives the native hosts an advantage over other hosts and gives synthetic biology approaches unique challenges. For the chain‐elongated GLSs, which include the health‐promoting 4MSB, the ability to control the number of cycles in the iterative process constitutes an additional challenge.GLSs production through plant cell or hairy root cultures have improved in some species of brassicaceous plants, particularly cress species. Unfortunately, they are still far from economically sustainable in large‐scale production and − for the most cases − have a complex mixture of different GLSs, which introduces the need for downstream purifications. Hence, engineering microbes represent an appealing alternative. Current reports indicate that tremendous optimizations are needed for this to be a viable option.In addition to classical optimization strategies such as media composition, growth conditions, and construct designs, other methods for greater production includes directed evolution on production hosts, metabolic flux analysis, as well as protein engineering to modulate enzyme kinetics and specification. These options involve testing production in hundreds − if not thousands − of mutants in high‐throughput screening platforms. This is made feasible only by emerging computational software and robotic laboratory equipment. New biotechnology tools are expected to enable high‐level production of glucosinolates in the near future.


Autism is a neurodevelopmental condition characterized by atypical brain functional organization. Here we investigated the intrinsic indirect (semi‐metric) connectivity of the functional connectome associated with autism. Resting‐state functional magnetic resonance imaging scans were acquired from 65 neurotypical adults  and 61 autistic adults . From functional connectivity networks, semi‐metric percentages (SMPs) were calculated to assess the proportion of indirect shortest functional pathways at global, hemisphere, network, and node levels. Group comparisons were then conducted to ascertain differences between autism and neurotypical control groups. Finally, the strength and length of edges were examined to explore the patterns of semi‐metric connections associated with autism. Compared with neurotypical controls, autistic adults displayed significantly higher SMP at all spatial scales, similar to prior observations in adolescents. Differences were primarily in weaker, longer‐distance edges in the majority between networks. However, no significant diagnosis‐by‐sex interaction effects were observed on global SMP. These findings suggest increased indirect functional connectivity in the autistic brain is persistent from adolescence to adulthood and is indicative of reduced functional network integration. We first assessed semi‐metric behavior at the whole‐brain level, then sequentially decomposed the semi‐metric connectome into hemispheres, networks, and nodes to ascertain the pattern of differences in brain regions. In light of the developmental hypothesis of functional connectivity in autism that suggests that autistic adolescents and adults display similar deviation patterns of intrinsic functional connectivity  Is there any difference between autistic adults and typical developing (TD) participants in terms of semi‐metric edges of the functional connectome? (b) Does biological sex affect these differences? (c) What is the pattern of differences in semi‐metric edges? (d) Are these altered semi‐metric connections weak or strong, long or short edges? To this end, we explored the semi‐metric behavior of the functional connectome in a sample of sex‐balanced autistic adults  after providing written informed consent Table , 2013. A2.2All MRI data were acquired using a 3 T GE Signa scanner  at the Cambridge Magnetic Resonance Imaging and Spectroscopy Unit. For the resting‐state functional MRI scan, participants completed a 13 min 39 s scan (625 volumes) with an echo‐planar imaging sequence using the following parameters: repetition time = 1,302 ms; echo time = 30 ms; flip angle = 70°; matrix = 64 × 64; field of view = 240 mm; 22 axial slices; slice thickness = 4 mm; slice gap = 1 mm. The first five volumes of each resting‐state acquisition were discarded to allow for equilibrium of the magnetization leaving 620 volumes for analysis. During acquisition, participants were instructed to rest with eyes closed, but not fall asleep. We also obtained the high‐resolution T1 MRI images utilizing the Driven Equilibrium Single Pulse Observation of T1 (DESPOT1) mapping technique as described in previous studies ; nuisance signal regression of the six motion parameters and their first order temporal derivatives and ventricular cerebrospinal fluid signal; and high‐pass frequency filtering with a cutoff frequency of 0.02 Hz. The mean framewise displacement (FD) estimated during head motion correction and mean DVARS, the frame‐by‐frame whole‐brain signal change of the denoised preprocessed data, were calculated for each participant  using a functional atlas . Nonparametric permutation testing  was applied to assess the significance of the model coefficients.We constructed a general linear model to test for SMP differences between autism and TD groups:We also examined the age effects on global SMP by using a three‐way interaction model:Since no significant age‐related interaction effect was observed, we used the two‐way interaction model in the following analysis for simplification, and age was included as a covariate in the general linear model.2.8i and j exceeded a given threshold then this edge was kept in the functional connectome, if not it was set to 0 denoting the absence of direct functional connectivity between the two nodes. We then calculated the SMP for these functional connectomes and an identical general linear model was then applied to explore the main effects of diagnosis on global SMP. A complementary analysis thresholding strong edges was also performed to provide additional support for the relationship between functional connectivity strength and SMP. As previously, nonparametric permutation testing  was applied to assess the significance of statistical model.To identify the strength of links contributing to semi‐metric topology, we derived a set of functional connectomes thresholding the connectivity  across the range 0–1 with an increment of 0.01. If the connectivity between regions r < R0. The general linear model was then applied on semi‐metric edge length to explore the main effect of diagnosis. Nonparametric permutation testing  was applied to assess the significance of statistical model with the statistical significance set at p < .05. To assess the effect of the number of edges, we plotted the distribution of correlation coefficients for each participant, and compared the edge number between autism and TD groups.In view of the dependency between distances and functional connectivity abnormalities observed in previous neuroimaging studies of autism  were again performed to test for group differences. The statistical significance was set at 2.9p < .05.To illustrate the sensitivity of SMP in detecting autism‐related differences, we additionally performed conventional network analysis on the whole‐brain, fully connected, weighted functional connectome using the GRETNA package , sex , and age , or effect of FIQ  was found. Post‐hoc analyses showed that autistic individuals had significantly increased SMP compared with the TD group , between sex and age , or among diagnosis, sex and age  on global SMP.Post‐hoc analysis for the main effect of age showed that whole‐brain SMP exhibited an age‐dependent reduction. The relationship between age and whole‐brain SMP was plotted for each group controlling for sex and FIQ Figure c. All th3.7F = 0.67, p = .42), main effect of sex , or interaction effect between diagnosis and sex  was observed on the threshold of functional connectivity graph that first separated the connectome into unconnected subgraphs.Compared with the TD group, autistic individuals showed significantly higher SMP when removing low strength edges from the connectome in the threshold range 0–0.1 Figure a. In bot3.8F = 3.79, p = .058), normalized clustering coefficient F = 1.44, p = .24), normalized shortest path length F = 2.54, p = .12), small‐worldness F = 3.69, p = .058), global efficiency , and local efficiency . No significant interaction effect between diagnosis and sex was observed in clustering coefficient , normalized clustering coefficient F = 1.33, p = .26), normalized shortest path length F = 2.10, p = .15), small‐worldness F = 2.83, p = .09), global efficiency , and local efficiency .Conventional graph theory analysis of whole‐brain unthresholded functional connectomes showed no significant differences between autism and TD groups in clustering coefficient ; he holds stock in GSK. All other authors have no conflict of interests to declare.Data S1 Table S1. Factorial analysis of variance in SMP at other frequency scales.Figure S1. Node and network definitions.Figure S2. Relationships between age and SMP at the hemisphere level for all participants. The effects of diagnosis, sex, diagnosis‐by‐sex and FIQ were regressed out from the model.Figure S3. Edge length and distribution of all edges (A) and metric edges (B). Line plot denotes the relationship between correlation coefficients and edge length, and histogram denotes the average number of edges within‐group. +, significant main effect of diagnosis on edge length ; ×, significant main effect of diagnosis on number of edges .Figure S4. Regions with incomplete coverage across participants. Each of eight networks has several regions, primarily located in the parietal lobe and cerebellum, that did not have full coverage in all participants.Click here for additional data file.Data S2: Supporting InformationClick here for additional data file.


A body weight gain of ≥15 kg between 20 and 50 years of age  and baseline  was significantly associated with increased CRC risk. BMI trajectory analyses revealed that the CRC risk increased gradually over the three BMI trajectories  compared with subjects who maintained a normal BMI. Being overweight/obese at the onset of adulthood and BMI trajectories over the lifespan that result in obesity lead to an increased CRC risk.Obesity is correlated with increased colorectal cancer (CRC) risk, but few studies have investigated lifetime body mass index (BMI) metrics and CRC risk. In a cohort of 139 229 subjects in the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial, we analysed the effects of life-course BMI trajectories on CRC risk. At 13 years of follow-up, 2031 subjects developed CRC. Compared with subjects who were never overweight/obese, subjects who first exceeded the threshold of 25 kg m The subjects completed a baseline questionnaire consisting of questions on demographic characteristics and CRC characteristics  and were histologically confirmed via medical record reviews .7 We divided the BMI values (kg m−2) at the three analysed age points into four categories according to the World Health Organization criteria: underweight (<18.5 kg m−2); normal ; overweight (25 to 29.9 kg m−2); and obese (>30 kg m−2). Weight changes during adulthood were classified as loss (≤−2 kg), stable , gain (≥5 to <15 kg), and notable gain (≥15 kg)8 (BMI was ascertained from self-reported questionnaires completed by the participants in the PLCO study.≥15 kg)8 .9 As a result, four trajectory categories  were ultimately obtained.10 All the P values were two-sided, and the results were considered significant at P < 0.05. The analyses were performed using SAS version 9.4  .Hazard ratios (HRs) and 95% confidence intervals (CIs) for CRC risk were estimated using Cox proportional hazard regression models to evaluate the relationships of age-specific BMI, average BMI, and weight change with CRC risk. To identify subjects with similar patterns of BMI development through the ages of 20 and 50 years and baseline, BMI trajectories based on the latent class growth model were generated with PROC TRAJ .−2, respectively (Supplementary Table P > 0.05).This study tracked a total of 139 229 subjects and included 2031 cases. The age at trial entry was 62.6 ± 5.3 years, and the BMIs at the ages of 20 and 50 years and at baseline were 22.1 ± 3.0, 25.9 ± 4.2, and 27.3 ± 4.7 kg m11 Specifically, compared with subjects who were never overweight/obese, subjects who first exceeded the threshold of 25 kg m−2 at age 20 had a higher CRC risk  (Supplementary Table −2 increase) compared with normal-BMI subjects .Ptrend (Ptrend = 0.005) is statistically significant.Age-specific BMI trajectories are illustrated in Fig. Furthermore, stratified analyses by demographic characteristics  showed little connection to BMI and CRC risk, and a subanalysis by CRC characteristics  did not reveal significant associations between BMI and CRC risk (Supplementary Tables 12 However, the weight of a subject might change over his/her adult life, and weight as a dynamic variable might play a critical role in the onset and progression of CRC.13 Therefore, our study expanded on prior studies assessing the association of BMI metrics across the adult lifespan with CRC risk.The results obtained for age-specific BMI, average BMI, body weight change, and BMI trajectory indicate a significant positive relationship between increased BMI and CRC risk if the subjects became overweight/obese at the onset of adulthood. Prior studies performed a dose–response analysis at a single time point in adulthood to demonstrate that an elevated BMI increases CRC risk.14Based on the abovementioned study, a BMI trajectory analysis was performed in this study, and the findings revealed that subjects with a normal or overweight BMI at the onset of adulthood that became obese by baseline have a higher CRC risk, suggesting that being overweight before adulthood could have biological effects on growth or be caused by an increased duration of excess weight.10 These findings may help young adults reduce CRC risk by focusing on body weight loss. We relied on self-reported body weight and height, which potentially introduced misclassifications in our assessment of BMI and might have limited the ability to investigate the association in this study.15 Another limitation is that we lack data for other measures of excess body fat, which might provide greater insight into the connection between excess body fat and CRC risk. Additionally, underlying diseases or lifestyle characteristics may cause weight loss, which affects the association between BMI trajectory and CRC risk.To our knowledge, a cohort study reduces the probability of recall bias, and this study might be suitable for examining the association between different BMI metrics over a subject’s lifespan and CRC risk.In summary, this study suggests that becoming overweight/obese in early adulthood might affect the incidence of CRC and that body weight gain over the adult lifespan is associated with a slightly elevated CRC risk. These findings offer a significant strategy to aid the primary prevention of CRC in subjects with a high BMI starting at early adulthood.Supplementary materials


Glomerular filtration rate (GFR) is a valid indicator of kidney function. Different factors can affect GFR. The purpose of this study is to assess the direct and indirect effects of GFR-related factors using structural equation modeling.We analyzed data from the baseline phase of the Ravansar Non-Communicable Disease cohort study. Data on socio-behavioral, nutritional, cardiovascular, and metabolic risk factors were analyzed using a conceptual model in order to test direct and indirect effects of factors related to GFR, separately in male and female, using the structural equation modeling.m2. GFR for 0.2, 11.3, 73.0 and 15.5% of people were < 30, 30 − 59, 60 − 90 and >90, respectively. Hypertension and aging in both sexes and atherogenic factor in males directly, and in females, directly and indirectly, had decreasing effects on GFR. Blood urea nitrogen and smoking in male and female, directly or indirectly through other variables, were associated with a lower GFR. In females, diabetes had a direct and indirect decreasing effect on GFR. Obesity in females was directly associated with upper and indirectly associated with lower GFR.Of 8927 individuals who participated in this study, 4212 subjects were male (47.20%). The mean and standard deviation of GFR was 76.05 (±14.31) per 1.73 According to our results, aging, hypertension, diabetes, obesity, high lipid profile, and BUN had a decreasing direct and indirect effect on GFR. Although low GFR might have different reasons, our findings, are in line with other reports and provide more detailed information about important risk factors of low GFR. Public awareness of such factors can improve practice of positive health behaviors. Increased prevalence of chronic kidney disease (CKD) is associated with an increased number of deaths as well as other complications in the form of other chronic conditions including cardiovascular diseases. Glomerular filtration rate (GFR) is a valid indicator of kidney function , 2. eGFRBased on the results of previous studies, GFR depends (directly and/or indirectly) on several factors. One of the methods for assessing direct and indirect effects of relevant factors on GFR is the structural equation model (SEM). SEM is one of the most useful methods for the concurrent testing of complex relationships between variables and assessment of the effect of latent variables . SEM is For the purpose of this study, data from the baseline phase of Ravansar Non-Communicable Disease (RaNCD) cohort study was used. Ravansar, a city in Kermanshah Province is located in the western part of Iran close to the border with Iraq with a population mainly comprised of Kurdish ethnicity. RaNCD cohort is part of the large PERSIAN  study. The data used in this study pertained to more than 10,000 participants aged 35 to 65 who had voluntarily entered the study and signed informed consent forms for participation. The study began in November 2014 and continues to date. Data from the recruitment phase of the study has been collected and includes general data, nutrition questionnaire, and biological samples. More information is available in the cohort protocol –18.Anthropometric indices were determined by bioelectric impedance device. The subjects’ heights were measured by a stadiometer with an accuracy of 1 cm. Body mass index (BMI) was calculated by dividing weight (kg) to squared height (m) . ParticiWaist to hip ratio (WHR) was classified to either normal or abnormal, according to the third report of the National Cholesterol Education Program (NCEP) on diagnosis, evaluation and treatment of high blood cholesterol in adults (Adult Treatment Panel III) in female and in men . AccordiPhysical activity calculated according to individual activity per day based on the 22-item questionnaire. Finally, metabolic equivalent of task (MET), as an indicator for level and measure of physical activity, were extracted and entered the model. MET is the amount of oxygen consumed at rest (about 3.5 ml 02/kg/min) and equals to resting metabolic rate. MET for each activity was extracted using compendium of physical activities .Nutritional status was determined according to a valid and reliable food frequency questionnaire customized to the local culture . ConsumpP-value less than 0.05 was considered as statistically significant. As the percentage of missing data was less than 2%, it was excluded from analysis.Spearman’s rank correlation was applied, and stepwise linear regression was obtained to assess the associations between the study variables and to implement the conceptual framework. Then, structural equation modeling (SEM) was used with maximum likelihood estimation (MLE). SEM includes causal modeling, analysis of covariance structures, and latent variable models. This model is a generalization of multivariate regression that allows one to estimate the strength and sign of direct and indirect effects for complicated causal schemes with multiple dependent and independent variables . In ordeOut of 8927 individuals participated in this study, 4212 (47.20%) subjects were males and 4715 (52.80%) subjects were females. The mean of age was 48.2 ± 2.10 (range:35–65). Prevalence of hypertension in females and males was 16.35 and 10.22%, respectively. Prevalence of BMI was 37% in females and 16.61% in males. The mean of atherogenic coefficient was 187.80 in females and 180.12 in males. Table Structural equation modeling (SEM) with maximum likelihood estimation (MLE) was applied to assess the conceptual model Fig. . ConfirmP values were estimated using tow-way analysis variance or test. BUN: Blood Urea nitrogen; PA: physical activity; BP: Blood pressure; AF: atherogenic Factor; WHR: Waist to hip ratio; BMI: Body mass index; PBF: Percent body fat; GFR: glomerular filteration rate.Table Figure For females, atherogenic index had a direct (β =  − 0.19) and indirect (β =  − 0.01) decreasing effects via BUN, high blood pressure, diabetes and obesity as an intermediate variables on eGFR. BUN had direct β =  − 0.22) and indirect (β =  − 0.02) decreasing effects via hypertension on eGFR. Hypertension was associated with lower eGFR (β =  − 0.12). Diabetes had direct (β =  − 0.04) and indirect (β =  − 0.02) decreasing effects on eGFR. Obesity had direct positive (β = 0.10) and indirect negative (β =  − 0.02) effects on eGFR. Diabetes and BUN were associated with high blood pressure . For males, atherogenic index had a direct negative effect (β =  − 0.13) on GFR. BUN had direct (β =  − 0.17) and indirect (β =  − 0.01) negative effects via high blood pressure, as an intermediate variable, on GFR. Hypertension decreased directly (β =  − 0.12) GFR. Smoking had a direct and indirect decreasing effect (β =  − 0.02 and β =  − 0.005) effects, via obesity and high blood pressure, as intermediate variables, on GFR. Physical activity had a direct negative (β =  − 0.20) effect on obesity . Meat consumption in females had a direct (−0.01) and indirect (−0.03) effect on GFR   in both genders. The findings of our study showed that obesity, diabetes, blood urea nitrogen, atherogenic factor, hypertension, meat consumption, and smoking were associated with lower GFR.Several risk factors  can affect on eGFR which has been reported from studies elsewhere . MultivaIn the current research, obesity in females had direct (positive) and indirect (negative) effects, via hypertension and diabetes, on GFR. Results from studies on the effect of obesity on GFR are not similar , 35. IseA meta-analysis showed that there is a U-shape relationship between eGFR and death rate; eGFR< 60 ml/min/173 m2 increases death rate incrementally, but eGFR> 105 ml/min/173 m2 results in a sharp decrease in death rate .In the RaNCD cohort study, low value of eGFR in females was due to inadequate physical activity and high prevalence of metabolic risk factors such as obesity, high blood lipids, and hypertension. eGFR was also related to BUN which had a negative direct and indirect relationship with GFR in both males and females. The value for BUN is, in fact, a sign of proper kidney functioning. The main causes of increased BUN are high-protein diets, low GFR, and congestive heart failure. An increase in BUN may be independent of changes in creatinine and GFR. Such increase is due to reabsorption from proximal tube through the activity of renin-angiotensin-aldosterone sympathetic nervous systems . There iDyslipidemia is an important risk factor for cardiovascular disease and CKD. In a study of 12,728 subjects with a 2-year follow up, it was found that high triglyceride and low HDL both were risk factors for increased creatinine. These lipid profiles had confusing effects on creatinine after adjustment for other risk factors . The mecIt is worth noting that this study is the first study that uses SEM for assessing the risk factors associated with GFR. The most important strength of the present study was the sample size which was large enough to investigate the association between all the above-mentioned variables with GFR. Using SEM and path analysis, we were able to investigate both direct and indirect effects of GFR risk factors. However, our study suffered from the following.Using a cross-sectional study, we were unable to confirm that the studied exposures had an exact causal relationship with the level of eGFR. The researchers’ definition of eGFR was only based on serum creatinine criterion which could lead to biased classification. Other studies have shown that eGFR measurement for subjects with normal kidney functioning was performed with less accuracy than those with CKD. Nevertheless, it was more accurate than serum creatinine or Cockcroft-Gaultequation.Findings of the present study confirmed the results of previous studies on the risk factors of eGFR including hypertension, diabetes, blood lipids, BUN, obesity and smoking. Although low eGFR might have different reasons and is not a consistent sign of CKD, our findings are in line with reports from elsewhere and provides more detailed information about important risk factors of low GFR. Awareness about such risk factors will lead to positive health behavior in general public. Future studies are recommended to investigate the effect of other variables including medications and food on eGFR.


Bactrocera tryoni (Froggatt)  is the most significant insect pest of Australian horticulture. Bactrocera tryoni is controlled using a range of tools including the Sterile Insect Technique (SIT). Mass-rearing and irradiation of pupae in SIT can reduce the fitness and quality of the released sterile insects. Studies have also showed reduced microbial gut diversity in domesticated versus wild tephritids.The Queensland fruit fly, Enterobacter sp. and Asaia sp. shortened larval development time, while this was delayed by Lactobacillus sp., Leuconostoc sp. and a blend of all four bacteria. The mean time from egg hatch to adult eclosion was significantly reduced by Leuconostoc sp. and the blend for males and females, indicating that the individual bacterium and consortium affect flies differently depending on the life stage . There was no impact of bacterial supplemented larvae on pupal weight, emergence, flight ability, or sex ratio.Transmission electron microscopy confirmed the presence of the bacterial isolates in the mid-gut of mass-reared larvae, and plate counts from individual larval guts showed increased numbers of bacteria in supplemented larvae. Several developmental and fitness parameters were tested including larval development time (egg-hatch to pupation), pupal weight, emergence, flight ability, sex-ratio, and time to adult eclosion (egg-hatch to adult eclosion). B. tryoni can impart fitness advantages, but the selection of probiotic strains  is key, as each have varying effects on the host. Bacteria added to the larval diet particularly Leuconostoc sp. and the blend have the capacity to reduce costs and increase the number of flies produced in mass-rearing facilities by reducing time to adult eclosion by 1.3 and 0.8 mean days for males, and 1.2 and 0.8 mean days for females.Our findings show that bacteria fed to the larval stage of  Bactrocera tryoni Froggatt  is native to Australia, and is a pest and biosecurity threat to its $9 billion horticultural industry [Bactrocera tryoni is controlled using a range of tools including the Sterile Insect Technique (SIT). SIT involves area-wide, inundative releases of irradiated, i.e. sterile insects to reduce reproduction in a wild population of the same species [The Queensland fruit fly, industry . Bactroc species . Domesti species . They al species .Citrobacter freundii, Enterobacter sp., and Klebsiella pneumonia to mass-reared Mediterranean fruit fly, Ceratitis capitata Wiedemann larvae , showed increased male and female pupal weight, larger sized males, increased lab survival under stress, and enhanced male sexual performance [Klebsiella oxytoca increased mating competiveness of bacterial supplemented sterile adult male C. capitata for wild females against wild males, inhibited female receptivity more efficiently than sugar only fed males, and increased survival under stress [Enterobacter sp. to C. capitata larvae reduced male larval development time, however did not impact pupal weight, flight ability, laboratory survival under stress, or mating competitiveness [Enterobacter sp. was also a target probiotic fed to larvae of Zeugodacus cucurbitae Coquillett (melon fly) with significant increases in pupal weight, survival rate, and size of flies were significantly increased [Gut bacteria in particular have been recognised for their effects on the physiology of tephritids across all the developmental phases from egg to adult. These include increased larval weight of flies produced from surface sterilised eggs vs non-surface sterilised eggs , reducedformance . Anotherr stress . A studytiveness . Enterobncreased . Althougncreased . FurtherB. tryoni and fed to mass-reared larvae, on larval development and several standard quality control parameters of the larval, pupal and adult stages used in SIT programs [The aims of the current study were to test the effects of bacteria sourced from wild larval programs .B. tryoni gut  and utilised as a larval probiotic in this study, clustered with Asaia sp., Enterobacter sp., Lactobacillus sp. and Leuconostoc sp. clades respectively in the 16S rRNA maximum parsimony phylogeny , although this was not significant for Leuconostoc sp.  . Enterobacter sp. and Asaia sp. reduced LDT, while Lactobacillus sp., Leuconostoc sp. and the blend delayed this parameter  than the control . However, the mean pupal weight of B. tryoni supplemented with the bacteria were all lighter than the control , with the lightest pupae those supplemented with Lactobacillus sp. .Pupal weight did not differ between the bacterial groups . The fastest eclosing B. tryoni females were also those supplemented with Leuconostoc sp. or the blend with 22.8 and 23.2 days respectively, compared to 24 days for the control females .All bacteria supplemented ol Figs.  and 6. TB. tryoni did not differ to the control (df = 25 F1.09 p = 0.390). All bacterial groups had mean emergence ≥95% (Table The mean number of bacteria supplemented emerged adult B. tryoni supplemented with bacteria did not differ to the control (df = 25 F = 0.956 p = 0.463). Mean flight ability was ≥91% for all bacterial groups (Table The mean flight ability of adult p = 0.782)  after supplementation with a strain of Enterobacter sp. in the larval diet, particularly of males [The present study demonstrated that wild bacteria supplemented larval . tryoni . Additiod humans , 20–22. of males . High leB. tryoni larvae supplemented with bacteria did not impact pupal weight, emergence, flight ability or sex ratio. Conversely, Z. cucurbitae, Enterobacter sp. fed to larvae was found to increase pupal weight [C. capitata larvae supplemented with a blend of Citrobacter freundii, Enterobacter sp. and Klebsiella pneumoniae also found an increase in pupal weight [C. capitata with larvae fed a single strain of Enterobacter sp. found no difference in pupal weight [B. tryoni [B. tryoni, higher pupal weight has been found to be positively related to higher emergence and flight ability [In the current study, l weight , and a sl weight . Anotherl weight . In our . tryoni . In mass ability . The thr ability –8. Howev ability , and incAsaia, Leuconostoc, and until recently Lactobacillus. Strains of Asaia are common insect symbionts [Leuconostoc are not widely known from tephritids. In the few studies available they were identified from laboratory-reared and wild flies that were fed fruit at the larval stage [Lactobacillus affect several physiological and behavioural traits in tephritids and other Diptera. In a very recent study, Lactobacillus plantarum inoculated in to the larval diet of the tephritid Dacus ciliatus (cucurbit fly) was found to have negative effects on pupae production [Drosophila melanogaster, L. plantarum had positive effects including increased mating duration and induced higher short-term offspring production, and when fed to parent flies L. plantarum were reported to modulate body mass of female offspring [Previous tephritid bacterial supplementation assays have not included strains from the genera ymbionts  and haveymbionts , 26. Stral stage –29. Straoduction . Conversffspring . This reB. tryoni larval midguts by TEM after being fed the bacteria enriched carrot diet . Similarly, the strain used proliferated in the larval gut, suggesting this environ is conducive to this bacteria. Most bacteria have an optimum pH 6–7 for growth, but several exceptions include lactic acid bacteria  and acetic acid bacteria (e.g. Asaia spp). that can proliferate effectively under acidic environments [Lactobacillus plantarum specifically has also been found to lower the pH of a tephritid larval diet from 5 to 4 after being added as a supplement [Asaia spp. are also common digestive tract associates of B. tryoni [B. tryoni mass-rearing [The target bacteria were observed in the iet Fig. , and thecrobiome . Enterobronments  and are pplement . Lactic . tryoni , and oth. tryoni , beetles. tryoni , mosquit. tryoni , 34, and. tryoni . The pH . tryoni  and ther-rearing . This te-rearing –39, howeB. tryoni have scope to be administered as part of SIT programs to produce high quality insects. However, the selection of the bacterial strains is key as they each have specific effects, particularly on development time. Further studies need to address the effects of supplemented wild bacteria on other traits including survival and mating competitiveness of B. tryoni [Bacteria fed to the larval stage of . tryoni . UltimatB. tryoni larvae were sourced from Redlands Research Station (RRS), Queensland. Infested apricots were sourced from Douglas Park, New South Wales. Individual third instar larvae had their midguts dissected and were lysed by hand with a sterile plastic mortar in 1 mL of sterile 1x Phosphate Buffered Saline (PBS). One hundred microliters of the resulting suspension was then spread on de Man, Rogosa and Sharpe agar  and trytone soy agar  plates in triplicate. Plates were incubated at 30 °C for 2–3 days. Single colonies were selected and subcultured on to MRS and TSA plates and incubated for 2–3 days at 30 °C. Pure cultures were deposited at the New South Wales Plant Pathology Herbarium, Orange Agricultural Institute, New South Wales, Australia (DAR) (Table Peaches infested with wild Asaia and Enterobacter) or MRS agar (Lactobacillus and Leuconostoc). RNA was extracted from a 5 mm3 sample of each isolate and placed in to 100 μL of Extraction Buffer , homogenised by hand with a sterile plastic probe for 10 s, then heated at 95 °C for 5 min. One hundred μL of Dilution Buffer  was then added. The 16S rRNA locus was selected for identifying the wild bacterial candidates to genus level. PCR amplification was performed in 10 μL final volumes. The primer pairs for amplification were FD1/rP2 or FD2/rP1 [Purified subcultures were grown in the dark at 25 °C for 4 days on TSA , birds, rodents and humans [Bacterial candidates from the genera . tryoni . Additiod humans , 20–22. Bactrocera tryoni larvae were reared on a standard diet comprising 338 g dehydrated carrot (bulking agent), 60 g of Torula yeast, 2.5 g sodium benzoate, and 600 ml of water [Asaia sp. and Enterobacter sp. cultures were grown on TSA plates, while the Lactobacillus sp. and Leuconostoc sp. cultures were grown on MRS agar plates for 3 days at 30 °C. The choice to use live bacteria in the larval diet was based on the observation of advantages of feeding live vs dead bacteria to tephritid larvae [3) of the Asaia and Enterobacter cultures were transferred to 30 mL sterile TSB, while the Lactobacillus and Leuconostoc cultures were transferred to 30 mL sterile MRS broth. Cultures were placed in a shaking incubator for 24 h at 30 °C and 30 rpm. After incubation tubes were centrifuged for 5 mins at 4000 rpm. The broth supernatant was removed, and the pellet washed with 30 mL of PBS, and centrifuged for 5 mins at the same speed. The PBS supernatant was removed. Bacterial suspensions 1 × 108 colony forming units per mL were made in PBS. Colony forming units were determined via ocular density at 600 nm wavelength with a Versa Max microplate reader . Ocular densities and their corresponding colony forming units were determined with serial dilutions and plate counts. For washed bacteria suspended in PBS at a concentration of 1–2 × 108 colony forming units per mL the ocular densities were as follows: Asaia sp. = 0.1, Enterobacter sp. = 0.2, Lactobacillus sp. = 0.2, Leuconostoc sp. = 0.05.of water . IngrediB. tryoni eggs were sourced from the FFPF, oviposited by 2 week-old adult flies raised on carrot diet (same ingredients as above except the addition of citric acid at 9 g per kilogram of diet). All laboratory based experiments were run at 26 °C ± 1 °C, 65% ± 5% relative humidity, and 10:14 light:dark cycle.Mass-reared B. tryoni eggs per replicate were randomly selected, twelve replicates per bacterial group. Circular black filter paper 90 mm in diameter was cut into quarters and autoclaved. Each quarter was moistened with 0.5 mL sterile water. One hundred and fifty eggs were placed on top of the moistened filter paper. Each quarter of filter paper containing eggs was then inverted, so that the eggs were in direct contact with the carrot diet in the agar plates. The lids of the agar plates were placed on top of the diet to maintain humidity during the egg hatch period. After 2 days, the lids were removed. Larval development time was measured from the time of egg hatch to the day of pupation by counting the number of pupae on each day of pupation until all larvae had pupated. All larvae pupated over a six-day period.Seventy-two rectangular plastic take away containers (500 ml volume) with lids were prepared. Lids of the plastic containers had a 5 × 8 cm hole cut in the top, and a piece of white ‘Swiss voile’ polyester fabric 3 cm wider and longer than the container was placed under the lid to prevent the escape of larvae from the container. Thirty grams of autoclaved vermiculite was mixed with 60 ml sterile water and added to the base of each container. The bacteria enriched carrot diet, and the carrot diet without bacteria (control) were weighed in to sterile 90 mm petri dishes. The agar plates with carrot diet were then placed over the vermiculite inside the take-away containers. One hundred and fifty mass-reared Asaia, Enterobacter, blend and control groups, and an MRS plate for the Lactobacillus, Leuconostoc, blend and control groups. Plates were incubated at 30 °C for 2–3 days and the colonies that were morphologically identical  to Asaia, Enterobacter, Lactobacillus and Leuconostoc were counted and subcultured. To confirm identification of colonies, representatives were selected and sequenced using the 16S sequencing protocol previously described.Seven days after egg hatch (representing late third instar larvae) five individual larvae per bacterial group were surface disinfested in 70% ethanol for 1 min, then rinsed in PBS. Larvae were transferred to 200 μL PBS and homogenised by hand with a sterile plastic mortar. Serial dilutions were prepared  of the original extract. Fifty microliters of the original extract and of each dilution were aliquoted on to a TSA plate for the Larval midguts were cut into 2 mm sections and placed overnight in Karnovsky’s fixative. Sections were rinsed in 1× PBS for 5 min (repeated three times) and placed in 1% buffered Osmium tetroxide for 4 h on a shaker. Sections were rinsed in deionized water for 5 min (repeated three times), immersed in 2% uranyl acetate for 1 h, then dehydrated in an ethanol series starting from 30 to 100% and finally in acetone. Sections were immersed in 50% acetone/Spurr’s resin mixture and shaken for 1 h, then fixed in pure resin and placed at 70 °C for 30 min, embedded in resin filled moulds, and polymerized overnight at 70 °C. Resin blocks were trimmed and 70 nm sections placed on 300 mesh copper grids, stained with 2% uranyl acetate, followed by Reynold’s lead citrate, washed in deionized water, and blot dried. Sections were visualised under a Philips 208 transmission electron microscope.Pupae were weighed individually 7 days after pupation, corresponding to the time that pupae in the FFPF are weighed for quality control purposes. Six replicates, each comprising 50 pupae per bacterial group were weighed, totalling three hundred pupae per bacterial group.3 mesh cage . Fliers that escaped the flight tube were collected daily over 6 days, until no more flies left the flight tubes. The number of fliers, non-fliers, part-emerged, and deformed were recorded and sexed. Flight ability was calculated as the number of fliers of the total pupae per bacterial group.One hundred and fifty pupae were selected with 6 replicates per bacterial group . Emergence and flight ability were calculated as mean percentages, and sex ratio was calculated as a ratio of the total pupae. Time to adult eclosion was determined by counting the number of adults  eclosing on each day for each bacterial group. Flight tubes were set up as in  with one3 Bugdorm cages (one cage per replicate). Pupae were counted on each day of eclosion and sorted by sex. All adults eclosed over a six-day period.One hundred and fifty pupae were selected, 6 replicates per bacterial group  and placed in 30 cmR 3.3.3  was used


Emotional enhancement of free recall can be context dependent. It is readily observed when emotional and neutral scenes are encoded and recalled together in a “mixed” list, but diminishes when these scenes are encoded separately in “pure” lists. We examined the hypothesis that this effect is due to differences in allocation of attention to neutral stimuli according to whether they are presented in mixed or pure lists, especially when encoding is intentional. Using picture stimuli that were controlled for semantic relatedness, our results contradicted this hypothesis. The amplitude of well‐known electrophysiological markers of emotion‐related attention—the early posterior negativity (EPN), the late positive potential (LPP), and the slow wave (SW)—was higher for emotional stimuli. Crucially, the emotional modulation of these ERPs was insensitive to list context, observed equally in pure and mixed lists. Although list context did not modulate neural markers of emotion‐related attention, list context did modulate the effect of emotion on free recall. The apparent decoupling of the emotional effects on attention and memory, challenges existing hypotheses accounting for the emotional enhancement of memory. We close by discussing whether findings are more compatible with an alternative hypothesis, where the magnitude of emotional memory enhancement is, at least in part, a consequence of retrieval dynamics. The fact that people are able to retrieve the gist of such scenes and describe them later, and that this ability is superior for emotional than for neutral scenes , the late positive potential (LPP), and the slow wave (SW), are known to be sensitive to visual attention and are robustly modulated by emotion . Participants provided informed consent and were reimbursed for their time and expenses by course participation credits or £15. Ethical approval was obtained from the University of Manchester Research Ethics Committee.Twenty‐five healthy adults, age 18–35, with no current or past history of neurological or psychiatric illness, were recruited through advertisements and the University of Manchester student credit participation system. Two participants were excluded because of technical failures during the recording. As described below, if any of the channels had more than 20% bad trials, that channel was excluded from analysis; participants who had more than one bad channel of those selected for analysis were excluded altogether. This approach led us to exclude one additional participant, leaving a final sample of 2.2Experimental stimuli consisted of 238 color images (size: 280 × 210 pixels), half of which conveyed negative valence and were arousing  and half of which were neutral in valence and not arousing . Participants judged emotional stimuli to be semantically related to each other  = 13.80, p < .001, η2 = .75; valence, t(31) = 15.46, p < .001, η2 = .79; and were equated for measures of semantic relatedness, t(27) = 1.32, p = .20, η2 = .03; see Table The emotional and neutral stimuli selected for use in the current experiment were significantly different on measures of arousal, t3 = 13.80,Stimuli were randomly allocated to 16 experimental lists: 8 mixed lists and 8 pure lists . Mixed lists contained two buffer stimuli  presented at the beginning of each list, and excluded from subsequent analyses to reduce the impact of primacy effects; followed by 12 stimuli—6 from the emotional and 6 from the neutral sets, in a randomized order. Pure lists contained 2 same‐valence buffer stimuli followed by 12 same‐valence stimuli . The allocation of stimulus to list type, the order of lists presented, and the order of stimuli within lists were randomized.http://www.vislab.ucl.ac.uk/cogent_2000.php).Stimuli were displayed on a 15″ × 12″ screen, which was positioned approximately 95 cm from the participant. Stimulus presentation and programming was realized using Cogent 2000 . Each picture was presented for 2,000 ms with a jittered ITI interval of 4,000 ms ± 500 ms. This long ITI was chosen, following Talmi and McGarry , to elim2.3.2free recall were presented on screen.After viewing the pictures, participants engaged in an arithmetic task, which aimed to eliminate the contribution of working memory to the recall output. Two simple sums were presented, one each on the right and left side of the screen. Participants were asked to compute the sums mentally and identify the highest value sum using two keys relating to the right or the left of the screen . A keyboard placed in front of the participant within comfortable reach allowed the participant to make their selections when prompted. The distractor task lasted for 60 s, after which the words 2.3.3The experimenter reentered the EEG chamber and asked participants to recall as many pictures from the previous list as they could remember, in any order and in as much detail as possible. Participants were asked to be specific in their descriptions of stimuli such that descriptions of two similar pictures should be distinguishable from their responses. Participants were given 3 min for this task.2.4http://www.biosemi.com) was used to measure EEG activity from the scalp using 64 electrodes and conforming to the 10–20 system embedded in an elastic cap  and baseline corrected. The mean amplitudes of the ERPs were extracted for each participant to represent the EPN, LPP, and SW. The time window for the EPN (150–350 ms), the LPP (400–700 ms), and the SW (1–5.5 s) were based on Schupp et al. .BioSemi ActiveTwo measurement system . Greenhouse‐Geisser correction was applied when necessary. A significance threshold of 33.1F = 28.50, p < .001, ηp2 = .58. The effect of list context did not reach significance, F = 4.06, p = .057, ηp2 =.16. As expected, there was a significant Emotion × List context interaction F = 33.12, p < .001, ηp2 = .61, and post hoc tests revealed that emotional enhancement of memory was significant and large in mixed lists, t(22) = 6.90, p < .001, ηp2 = .35, but not significant and small in pure lists, t(22) = 1.72, p = .10, ηp2 = .03  = 4.96, p < .001, ηp2 = .22, while more emotional stimuli were recalled in mixed compared to pure lists t(22) = 2.93, p = .01, ηp2 = .09.Free recall responses were scored following previous work  for every relevant trial type. Each condition we analyzed had 37 artifact‐free trials on average, with each participant contributing at least 21 artifact‐free trials in each condition. The subsample of N = 19 participants who were included in the analysis of EPN provided an average of 40.44 artifact‐free trials (SD = 3.98). Adding the factor of memory status  reduced the number of trials per cell substantially, so we could not justify an analysis of subsequent memory effects. We therefore limited ourselves to describing emotional modulation of attention regardless of subsequent memory. Extracted data corresponding to the EPN, LPP, and SW were entered to separate 2 (List Context: pure/mixed) × 2  repeated measures ANOVAs.Participants contributed an average of 39.78 artifact‐free trials  = 6.75, p = .18, ηp2 = .27. Neither the effect of list context nor its interaction with emotion was significant. The subsample analysis of hits qualitatively replicated these results, but here the effect of emotion was present only at a trend level, although it remained an effect of medium size, F = 3.33, p = .09, ηp2 = .23. Other effects were not significant.Extracted data from occipitoparietal electrodes were entered into a repeated measures ANOVA with the same factors as above Figure . In acco3.2.2F = 11.58, p = .003, ηp2 = .35. Neither the effect of list context, F = 3.49, p = .08, ηp2 = .14, nor its interaction with emotion reached significance. The subsample analysis of hits replicated these results with a significant and large effect of emotion, F = 5.51, p = 037, ηp2 = .31. Other effects were not significant.Extracted data from centroparietal electrodes were entered into a repeated measures ANOVA with the same factors as above Figure . Emotion3.2.3F = 8.40, p = .001, as the component decreases with time. The trend for a main effect of emotion did not reach significance, F = 3.81, p = .06, ηp2 = .15, but interacted significantly with time bin, F = 4.18, p = .009, ηp2 = .16, because it was stronger earlier in the epoch. No other effects were significant. To query the duration of the effect of emotion, we conducted separate repeated measures ANOVAs for each of the four time windows, with the factors of emotion and context. As expected, during the last second of picture presentation, the main effect of emotion was significant, F = 11.46, p = .003, ηp2 =.35; the other effects were not significant. The effect of emotion was no longer significant in the first second after picture offset (early ITI), F = 3.98, p = .06, ηp2 = .16, nor at any other subsequent time bin. The subsample analysis of hits replicated the obvious effects of time, F = 10.63, p = .001, ηp2 = .47, and here the main effect of emotion was significant, F = 6.31, p = .027, ηp2 = .34, but these two effects did not interact significantly and the effect size of the interaction was small. This result implies that, when events that are eventually remembered are considered separately from those that will subsequently be forgotten, emotion appears to influence scalp markers of attention all throughout the ITI, but given the small sample size, we should be cautious in interpreting the null interaction effect.The mixed emotion condition produced the highest amplitude, while amplitude in the mixed neutral condition was suppressed relative to all other conditions, an effect that was more pronounced earlier on in the SW epoch. Extracted data from centroparietal electrodes were entered into a 4 × 2 × 2 repeated measures ANOVA with the factors time bin , list context (mixed/pure), and emotion . The results are depicted in Figure 3.2.4p = .016). None of the correlations were significant. We note that cross‐participant correlations in a small sample such as the one used here are likely underpowered.We examined correlations, in mixed and pure lists separately, between memory and ERPs—namely, EPN, LPP, and (average) SW. The three correlations within each list context were corrected for multiple comparisons  = 12.96, p = .002, ηp2 = .42; N2: F = 6.32, p = .022, ηp2 = .26; P3: F = 6.75, p = .017, ηp2 = .24). For the P3, there was a trend toward a more positive amplitude in pure compared to mixed lists, F = 3.86, p = .06. No other effects were significant.The pattern that emerged when we examined additional components resembled the pattern that is already reported above Figure . Peak am4This study tested the hypothesis that the effect of list context on behavioral emotional memory performance is caused by an enhancement of selective attention toward emotional stimuli only in mixed lists but not in pure lists. We tested this hypothesis by examining the most widely known ERP correlates of motivated attention. The behavioral results replicated our previous work, demonstrating an emotional enhancement of memory in mixed but not pure lists. As we have observed previously, memory for neutral stimuli in mixed lists was decreased (a large effect size), and contributed to the interaction between list context and emotion, together with the increase in memory for emotional stimuli in mixed lists —a more subtle effect that is not always observed. In contradiction with our hypothesis, whereas list context modulated the effects of emotion on behavioral memory performance, it did not modulate the effects of emotion on neural indicators of emotion‐related attention at encoding. Replicating previous findings, emotion modulated the EPN, LPP, and the SW, which are established correlates of emotion‐related attention, as well as the N1, N2, and P3. Crucially, the emotional modulation of these ERPs was context independent, and statistically they were equally strong in pure and mixed lists. The same findings were obtained in an analysis that focused on subsequently remembered items, although we acknowledge that a more powered analysis of hits may expose context effects. These results refute both the suggestion that attention is no longer preferentially allocated to emotional stimuli in pure lists, and the suggestion that attention to neutral stimuli in mixed lists is severely depleted compared to attention to the same pictures in pure lists. List context here effectively created a functional dissociation between attention  and memory . These available results are intriguing because they impose constraints on models suggesting that additional attention to emotional items at encoding is the main determinant of emotional memory enhancement. We turn to these theoretical implications after we discuss the electrophysiological results in more detail.The finding that emotion modulated the EPN, LPP, and SW is important because this is the first study to examine the effect of emotion on these components during an intentional encoding task, in which participants have a reason to pay attention to neutral stimuli, and the first time the comparison neutral scenes were controlled for semantic cohesiveness. The emotion modulation of the LPP and SW is typically considered to be a result of bottom‐up modulation of visual attention; but when participants intentionally encode neutral items for a subsequent test, they could well recruit visual attentional resources through top‐down means. Indeed, in our recent fMRI study, the successful encoding of neutral scenes in mixed lists relied on top‐down attentional resources to a greater extent compared to the successful encoding of neutral scenes in pure lists  theory (Mather & Sutherland, 4.1Before we turn to the theoretical implications of our findings, we note that while the functional dissociation between the effect of emotion on attention and memory contradicted our initial hypothesis, the dissociation is not entirely unexpected. In fact, these results add to mounting evidence that the emotional enhancement of memory may not depend only on encoding dynamics. For example, in our previous work, we showed that arousal had direct effects on early long‐term free recall tests of memory even when attentional effects were covaried out statistically (Pottage & Schaefer, To answer these questions, we developed a temporal context model of emotional memory enhancement, called the emotional context maintenance model (Talmi, Lohnas, & Daw, These speculations about the way that context can help us retrieve unique episodic memories tie in well with literature showing that the prefrontal cortex contributes to emotional memory retrieval, and that its contribution can be valence specific (Dolcos et al., 4.2The experiment reported here has three main limitations. First, because we operationalized emotion using only negative emotionally arousing stimuli, we cannot be sure that they generalize for stimuli with positive valence. Although both positive and negative stimuli should capture attention, because this process is thought to be governed by emotional arousal rather than valence (Mather, Clewett, Sakaki, & Harley, Second, we have tested only immediate recall here, and therefore cannot be sure that the contextual influences on emotional memory extend in time to delayed tests. It is slightly tricky to replicate the current paradigm in a delayed test, because delayed testing requires carrying out all manipulations between subjects: participants who study one pure neutral list, one pure emotional list, and one mixed list in Session 1 cannot be instructed to consider only stimuli from one of these lists in Session 2. Thus, unless only a single list is studied in Session 1, recall in Session 2 would always be mixed. The relationship between immediate and delayed emotional memory effects is of inherent interest to the literature on emotional memory, and warrants additional research.Finally, unfortunately, we could not examine neural indices of successful encoding in our data, because many participants did not have either enough hits or enough misses to analyze the difference due to memory. It would have been useful to check whether this experiment replicates Watts et al. , and intIn conclusion, emotional stimuli are prioritized for processing regardless of their local context, but good encoding does not always translate to good memory performance. It is well known that memory performance depends intimately on the interplay of encoding and retrieval. Our data suggest that this interplay could play an important role in emotional memory enhancement.Deborah Talmihttp://orcid.org/0000-0002-7720-2706