However, HDV electrification does not reduce GHG emissions without enhanced emission-free electricity generation. In contrast, due to differing emission profiles, light-duty vehicle (LDV) electrification in China consistently reduces GHG emissions (~2 Mt CO2), but results in fewer air quality and human health improvements (145 avoided deaths). The calculated economic impacts for human health endpoints and CO2 reductions for LDV electrification are nearly double those of HDV electrification in present-day (155M vs. 87M US$), but are within ~25% when enhanced emission-free generation is used to power them. Overall, we find only a modest benefit for EVs to ameliorate severe wintertime pollution events, and that continued emission reductions in the power generation sector will have the greatest human health and economic benefits.Electric vehicle (EV) adoption promises potential air pollutant and greenhouse gas (GHG) reduction co-benefits. As such, China has aggressively incentivized EV adoption, however much remains unknown with regard to EVs’ mitigation potential, including optimal vehicle type prioritization, power generation contingencies, effects of Clean Air regulations, and the ability of EVs to reduce acute impacts of extreme air quality events. Here, we present a suite of scenarios with a chemistry transport model that assess the potential co-benefits of EVs during an extreme winter air quality event. We find that regardless of power generation source, heavy-duty vehicle (HDV) electrification consistently improves air quality in terms of NO Electric vehicles (EVs) offer potential air quality and climate change co-benefits, but due to varying power generation and vehicle types, and because air pollution chemistry is nonlinear, it is not clear to what extent EVs could provide mediation, especially during extreme air pollution episodes. China is both rapidly adopting EVs and frequently experiences poor air quality. We use an air quality model that simulates the complex interplay between weather and air quality to examine the potential co-benefits of EVs in China during a historical pollution episode. We simulate both light- and heavy-duty vehicle adoption to show their individual benefits, and demonstrate the need for low-emission electricity generation to maximize co-benefits. Overall, we find that heavy-duty fleet electrification consistently improves air quality and reduces mortality, but offers little climate change benefits without enhanced emission-free electricity generation. Light-duty vehicles, however, offer large climate change benefits but few air quality improvements, highlighting the need for cross-modal adoption strategies. CTM-based analyses of EV adoption in China are limited despite growing widespread deployment . The electricity sector emission rates reflect those from the Each simulation is run from December 22, 2012 to January 31, 2013, with the first 10 days discarded as model spin-up. Our control simulation is referred to as BASE. Our primary electrification (HDV_2015) experiment replaces a total of 1.5M HDVs (~40% of the fleet), with ~33% of these HDVs placed in cities from −1, which represents a new compact EV ; these parameters lead to an equivalent LDV adoption of 39.2M vehicles . Although the total electricity demand is the same between e-HDV and e-LDV experiments, the spatial distribution of the demand differs slightly due to differing intra- and inter-province fleet distributions. In general, LDVs are more concentrated in the most economically developed regions  is estimated as POP is the population exposed to the incremental concentration ΔC in the 12 km model grid cell i, IR is the incidence rate of the health endpoints, and β is the concentration-response function. For NO2, the only health endpoint we calculate is premature mortalty and our β values come from 2.5, we use updated, more conservative β values from https://sedac.ciesin.columbia.edu/data/collection/gpw-v4) and β and IRs are from a range of sources . The model is run with analysis nudging above the boundary layer using Four Dimensional Data Assimilation (FDDA) with nudging coefficients of 3.0 × 10−4 s−1 for temperature and winds and 1.0 × 10−4 s−1 for water vapor mixing ratio. The model physics options include the Morrison 2-moment microphysics scheme .Our experiments use the two-way coupled Weather Research and Forecasting  using the methods of 2.5 simulation biases. To remedy these biases, we smoothed the 50 largest anomalous values of each emitted species in each emission layer prior to merging with the unmodified onroad and power sector emissions. Anomalous values were smoothed by averaging the eight neighboring grid cells. Grid cell smoothing sensitivity tests were performed until a near-zero mean bias over Beijing was attained.Anthropogenic emissions were generated with raw inputs from EDGAR version 4.3.2 (2.4.https://www.ncdc.noaa.gov/isd/data-access). Our comparisons are with observations sites closest to the U.S. Embassy locations that measure PM2.5. Overall, the model performs very well for these variables at these locations. WRF generally underestimates surface temperatures (mean bias [MB] = −0.4 to −1.5) but matches daily variability well—correlations (r) range from 0.85 to 0.97. Relative humidity performance is good over Beijing , though over Chengdu, WRF is biased low by over 20% (r = 0.66). Wind speed is also simulated well, with MBs ranging from −1.2 to 0.2 m s−1 and high correlations, particularly over Shanghai and Guangzhou.2.5 time series for WRF-CMAQ as compared to surface observations from United States Embassy sites in Beijing, Shanghai, Guangzhou, and Chengdu . The model is biased high over three of the four locations, ranging from −0.7 μg m−3 (−0.4%) over Beijing to 88 μg m−3 (106%) over Guangzhou. The lowest (highest) bias generally occurs during midday (evening) when PM2.5 is at a minimum (maximum). Comparing the observed timeseries to the average time series of the nine grid cells around the observation site reveals extremely pronounced spatial variability that the emissions or model may not appropriately delineate. For example, Beijing’s bias decreases from −0.7 to −69 μg m−3; Shanghai from 65 to 21 μg m−3; Guangzhou from 88 to 67 μg m−3; and Chengdu from 33 to −8.4 μg m−3. Over Beijing, Shanghai, and Chengdu, WRF-CMAQ matches both the hourly  and daily (rday = 0.64–0.88) variability of PM2.5 well, but it performs poorly over Guangzhou (rday = 0.21). Comparisons with Guangzhou’s adjacent grid cells yield similarly poor agreement. We attempted to remedy the poor performance in the vicinity of Guangzhou by testing several WRF physics options , etc.). Using stronger nudging coefficients within the boundary layer and at the surface slightly improved the performance over Guangzhou in terms of matching daily variability, but doing so increased the bias in the four cities substantially, and so we retained our original parameters. We also perform a sensitivity simulation without the aerosol-radiation feedback, which reduces PM2.5 concentrations (and thus decreases the bias at three of the four sites), but it decreases the correlation at each site  are calculated as s at hour t and grid cell We construct our vehicle electrification emission datasets using the methods described in 2.5.1.fEVj,m is the fraction of the ICE vehicles in grid cell j and mode m converted to EVs, m, fEVj,m, we first determine the number of vehicles of each mode in each grid cell using GAINS vehicle fleet counts, which we map onto our 12 km grid using the on-road emissions of NOx (NO + NO2) as weights for HDVs; for LDVs, we use CO. We then choose the total number of ICEVs to transition and distribute them accordingly. First, we distribute a fraction of the total EVs to the 30 cities that collectively represent over 80% of the EVs in 2015  of species s for the EGUs in grid cell xj, and Vt,j is the marginal electricity generation (Wh) assigned to grid cell xj. We calculate x, SO2, total PM, the fraction of total PM that is PM2.5, PM10, and PM2.5–10, and the BC and OC fractions of PM2.5 for each province and EGU type. For model-simulated species without EGU emission rates , we assume a conservative scaling factor equal to the lowest emission increase (associated with and only applied to EGU emissions). Since PM2.5 emissions are highly speciated in the model emissions (18 species) but the EGU emission rates only provide the fraction of PM2.5 that is OC and BC, we set the emission rate of “PMOTHR”  equal to the emission rate of PM2.5 minus the emission rates of BC and OC. For some experiments (*2010), we set coal-fired EGU emission rates to those in 2.5 rate change between the two datasets. For CO2, we use 2 emission rate of coal-fired EGUs and 743.4 g kWh−1 , CE is the charging efficiency  of the adopted EV, fEVj,m as above is the fraction of the ICEVs transitioned to an EV, and VKTt,k,m is the vehicle kilometers traveled by mode m in grid cell xk and time t. wvkt), which scales the hourly VKT by its inverse ; that is, the diurnal cycle of EV charging (Q) and VKT are inversely proportional. The GAINS model provides province-level VKT, which we map onto our 12 km grid in the same way as with the vehicle fleet. EVeff is experiment dependent.The electricity need for the EVs in grid cell ncy 85%, , EVeff i3.3.1.2.5 concentrations range from ~10 μg m−3 over remote areas of China to ~200–350 μg m−3 over the North and Central China Plain (NCP) in our baseline historic scenario , modeled PM2.5 across Beijing exhibits a strong north-south gradient, ranging from ~50 μg m−3 in the north to over 300 μg m−3 in the south  . The combined monetary impacts of a CO2 increase  . However ton CO2 , a loss  ton CO2 .x and primary PM2.5. e-LDV adoption avoids 145  premature deaths due to a China-averaged PM2.5 (NO2) reduction of 0.16 ± 0.27 μg m−3 (0.02 ± 0.05 ppb). The adoption of e-LDVs avoids ~25% of the number of deaths as e-HDVs, however, e-LDVs dramatically reduce CO2 emissions (2.2 Mt Jan−1) such that the combined economic impacts of CO2 reductions and human health impacts yield a total savings of 156M US$ . Because of their substantially smaller per-kilometer electricity requirement, significantly more LDVs are electrified 39.2M; , though 156M US$ .2, PM2.5, NO2, and associated mortality changes favorable/extreme meteorological conditions.For a month with less extreme meteorology (January 2014), we find that e-HDV health gains are 14% less than those in 2013 due to a smaller reduction in domain-averaged PM1 μg m−3 . Thus, w2.5 changes and resultant avoided premature mortality due to acute PM2.5 and NO2 exposure are modest for this extreme event—a consequence of the small fraction of both primary and precursor PM2.5 emissions in the on-road sector  reduction is 4.0 μg m−3 (0.8 ppb), and 11.2 μg m−3 (3.0 ppb) over Beijing  by 21.2 μg m−3 (0.3 ppb) over China, by 25.1 μg m−3 (0.4 ppb) over EV adoption grid cells, and by 32.0 μg m−3 (1.2 ppb) over Beijing, leading to 7k+ avoided premature deaths and total health impacts of 3.4B US$ . Based on these CO2-neutral rates alone, it is clear that e-LDV adoption can achieve net-negative CO2 emissions much more readily than e-HDV. Indeed, all e-LDV scenarios can reduce CO2 emissions, except in a scenario when e-LDVs have low battery efficiencies and are solely powered by coal-fired EGUs prior to recent emission reductions . Likewise, the 50% decarbonized scenario for e-LDVs avoids 64.4 Mt yr−1 of CO2, 37.7 tons more than avoided by LDV_2015.CO2 emission rate of ~750 g CO2 kWh−1  with slightly larger reductions in EV-forward cities. NO2 changes over China (−0.12 ± 0.26 ppb) follow major roadways and are largest in the major metropolitan regions and EV-forward cities (−1.29 ± 0.76 ppb).The adoption of 1.5M e-HDVs in China decreases average PMg domain . Reducti2.5 changes over all of our averaging locations and all experiments are < 1 μg m−3, with increases for LDV_COAL and decreases for all other scenarios  experiencing little change or PM2.5 increases  does PMeriments . These reriments , while seriments ; that is2.5 air quality benefits occurs for most locations. Under HDV_COAL, many regions see an increase in PM2.5 compared to the domain-wide decreases for HDV_2015, although a swath from Beijing to Chengdu and the Shandong province still experiences PM2.5 decreases. For LDV_COAL, Beijing, Tianjin, and a few grid cells in Guangxi and Shanghai experience PM2.5 decreases, but the majority of the country’s average PM2.5 increases by over 2 μg m−3.Under scenarios with significantly higher EGU emission rates, the impact of high-emitting coal-fired units becomes more apparent, and the transition from net-positive to net-negative PM2 emissions, it has a surprisingly small impact on air quality in our simulations. To be sure, emission rates from the 2.5 (NO2) is reduced by 1.1 μg m−3 (0.2 ppb) over EV adoption cells which leads to 575 avoided deaths over China, 1.8× that compared to HDV_2010. For LDVs under 2010 emission rates, although NO2 decreases (−0.02 ppb) average PM2.5 increases (+0.63 μg m−3) resulting in mortality increases (59 deaths incurred), but slightly decreases in the REN scenario .While the benefits of enhanced renewable power generation are clear in terms of CO2.5 (95P) are substantially more heterogeneous  including a 15.5 μg m−3 reduction over Beijing. However, some areas near clusters of coal-fired EGUs in the North China Plain see large increases (>10 μg m−3), demonstrating a clear example of a “spillover effect”  and demonstrated the sensitivities of the actualized co-benefits of EV adoption to power plant emission rates. Overall, we have shown that the air quality benefits of EV adoption during the January 2013 are modest, with e-HDVs yielding air quality improvements for all power generation scenarios, and e-LDVs requiring emission rate reductions beyond 2010 levels  work  estimatex/VOC ratios differently, especially within the urban core. Other improvements are potentially more fundamental, such as designing the modeling framework to maximize use of the results by policymakers and stakeholders, as recent evidence suggests harmonization across studies could be improved  e-HDV adoption would reduce just ~1%–2% of these premature deaths, while removal of all on-road transportation sector emissions leads to an ~6% reduction in deaths. Removal of all energy sector emissions however, produces an ~24% drop in premature deaths. Clearly then, carbon- and pollutant-free energy generation is central to the actualization of air quality and climate co-benefits of vehicle electrification in China.China’s chemical landscape is rapidly evolving due to widespread industrialization and substantial pollutant remediation efforts at national and provincial levels. Due to policy-driven changes in energy sector emission rates alone, we find that in less than a decade the air quality benefits of e-LDV adoption switch from a net-negative to a net-positive. Further, air quality will likely continue to improve as the power generation sector decarbonizes and reduces allowable emission rates from fossil fuel-fired EGUs—indeed, an e-LDV purchased in 2013 will be “cleaner” in 2020 than when it was new. Moreover, if reduced fossil fuel-fired energy generation projections are actualized , by 2030he world . In termhe world . We estiSupplement11


The AMOVA showed the low but significant level of genetic differentiation among strains (3.79%). Bayesian clustering analysis using STRUCTURE classified the strains into 14 different clusters. The assignment test showed that 93.64% of the individuals could be assigned correctly into their original strain. Overall, our findings can be contributed to complementing scientific knowledge for conservation and management of threatened strains of common carp.Hungary is one of the largest common carp-production countries in Europe and now, there is a large number of local breeds and strains in the country. For proper maintenance of the animal genetic resources, information on their genetic diversity and structure is essential. At present, few data are available on the genetic purity and variability of the Hungarian common carp. In this study, we genetically analyzed 13 strains in Hungary and, in addition, the Amur wild carp, using 12 microsatellite markers. A total of 117 unique alleles were detected in 630 individuals. Low levels of genetic differentiation (F Nowadays many fish species and subspecies are endangered mainly due to habitat loss, overexploitation, pollution, and climate change ,2. As a Cyprinus carpio L.), one of the oldest domesticated species for aquaculture [The common carp  ,40. In tA total of 630 samples were collected from 13 Hungarian common carp strains, namely Biharugra scaly (BiS), Biharugra mirror (BiM), Böszörmény mirror (BoM), Hortobágy scaly (HoS), Hortobágy mirror (HoM), Hortobágy wild (HoW), Szarvas-15 (SZ1), Szarvas P3 (SzP), Szeged scaly (SzS), Szeged mirror (SzM), Hajdúszoboszló scaly (HaS), Hajdúszoboszló mirror (HaM), and Tata scaly (TaS) in five hatcheries  and the National Agricultural Research and Innovation Centre (NARIC), Research Institute for Fisheries and Aquaculture NAIK HAKI gene bank . We also collected samples of Amur wild carp (AmW) as outgroup for statistical analysis. Details on the number of samples of each strain, their abbreviations, and coordination of sample collection places for common carp are given in Tissue samples were obtained from fin clips. Approximately 0.5–3 cm of caudal fin clips were cut and preserved in 96% ethanol and stored at −20 °C until further laboratory analysis. The study was performed on the basis of the permit issued by the Hajdú-Bihar Megyei Kormányhivatal (reference number: 15/2019/DE MÁB). Sampling of fin clips was carried out after anaesthetizing the fish in clove oil solution (1 drop of concentrated oil to 1 L of water). Total genomic DNA was isolated from the fin clips using the EZNA Tissue DNA kit  following the manufacturer’s instructions. Concentration of the isolated gDNA was measured using a Nanodrop 1000 Spectrophotometer. Samples were diluted to 100 ng/μL for further use.A total of 12 microsatellite loci ,42 were 2 , 0.1 µL reverse and 0.1 µL fluorescent forward primer , 0.05 µL GoTaq Flexi DNA Polymerase , 2 μL genomic DNA (100 pmol/µL), and 5.05 µL sterile water up to a final volume of 10 μL. Thermal cycling conditions for each locus were DNA denaturation at 94 °C for 4 min, followed by 35 cycles of 94 °C for 30 s, annealing temperature , 1 µL 10x Gotaq Flexi Buffer , 0.7 µL MgClperature  for 30 sperature . The resis) with 95% confidence intervals using GenAlEx 6.41 [The deviation from the Hardy–Weinberg equilibrium (HWE) and linkage disequilibrium for all locus-strains were calculated using GENEPOP v.4.3 ,46. GenelEx 6.41 , FSTAT vlEx 6.41 , and POPlEx 6.41 . We appllEx 6.41  to accoust) and Cavalli–Sforza and Edwards’ genetic distance (D) [https://bioinformatics.org/groups/?group_id=84) to explore relationships among the strains [Pairwise genetic differentiation between strains were calculated using the Wrights fixation index (Fance (D)  using thance (D) . The denance (D)  with 100 strains ,53. Assi strains  to assig strains  the Mont strains  with 10,The patterns of genetic structure between strains based on allele frequency in microsatellite data were assessed using the analysis of molecular variance (AMOVA) with Arlequin 3.5.2.2 . One thoThe pattern of genetic structures among strains was assessed using the Bayesian approach in STRUCTURE 2.3.4 , with adAll 14 strains of common carp, in a total of 630 individuals, were successfully screened for 12 microsatellite loci, which were polymorphic in all strains. The analysis by MICRO-CHECKER  revealedp < 0.01). The mean number of alleles per each strain was 11. The lowest and highest mean number of alleles was observed for Hajdúszoboszló scaly (6.500) and Biharugra mirror (17.580), respectively. A total of 117 private alleles were detected for the 12 polymorphic loci in 630 individuals. The lowest and highest number of private alleles were observed in Szeged mirror and Hortobágy wild, respectively. The mean observed heterozygosity value (Ho) in the 14 strains was 0.840 with a range of 0.720 in Szarvas-15 to 0.990 in Böszörmény mirror. Additionally, the mean expected heterozygosity value (He) in all the strains was 0.800 with a range of 0.710 in Szarvas-15 to 0.890 in Hortobágy wild  ranged from 0.028 (between Biharugra mirror and Hortobágy mirror) to 0.231 , while the difference among strains within geographical groups was higher and significant . These results support the conclusion that a high level of genetic variation within strains is biologically typical for domestic common carp in the Carpathian Basin.AMOVA results  revealedp (X/K), using the preliminary STRUCTURE run, related with different numbers of genetic clusters K, calculated from structure analysis of 630 individuals showed the highest value at K = 14, which was followed by K = 2  and France ([st = 0.250). The low Fst values can be explained by the inadequate number of elements of the strains, the presence of null alleles, or genotyping error, but this indicator may affect the characteristic features of the strains sampled [In accordance with our results, previous studies reported low levels of genetic differentiation among several strains of common carp in the Czech Republic , ,67, 22,6STRUCTURE-based analyses  indicateCommon carp is the main fish species in pond aquaculture production in Hungary , where 3Overall, the microsatellite loci examined in our study proved to be quite effective in characterizing different genetic variabilities within and between the common carp strains. Our findings indicate relatively high values of expected heterozygosity for loci within common carp strains from Hungary. It is known that a stable polymorphism can be maintained if the effect of heterozygous advantage exists. It is also suggested that the applied fish farming practice is able to preserve and possibly improve a certain level of genetic diversity for generations ,81,82. I


Serum creatinine is suboptimal as a biomarker in the early diagnosis of contrast-induced nephropathy (CIN). In this study, we investigated a panel of novel biomarkers in the early diagnosis of CIN and in assessing patient outcomes. β2M, IL18, IL10, KIM1, and TNFα were determined using Luminex and ELISA assays. Outcomes were biomarker diagnostic discrimination performance for CIN and mortality after generation of area under receiver operating characteristic curves (AUROCs).  This single-centre, nested, prospective case-controlled study included 30 patients with CIN and 60 matched controls. Serum and urine samples were collected before contrast administration and at 24 hours, 48 hours, and ≥5 days after contrast administration. Concentrations of NGAL, cystatin C, p < 0.01) and 48 h β2M levels (p < 0.001) and baseline urine NGAL (p=0.02) were higher in CIN patients compared to controls with AUROCs of 0.75, 0.78, and 0.74, respectively, for the early diagnosis of CIN. Serum β2M levels were higher in CIN patients at all time points. Elevated baseline serum concentrations of IL18 (p < 0.001), β2M (p=0.04), TNFα (p < 0.001), and baseline urine KIM (p=0.01) and 24 h urine NGAL (p=0.02) were significantly associated with mortality. Baseline serum concentrations of IL18, β2M, and TNFα showed the best discrimination performance for mortality with AUROCs, all >0.80. Baseline NGAL was superior for excluding patients at risk for CIN, with positive and negative predictive ranges of 0.50–0.55 and 0.81–0.88, respectively. Cystatin C (p=0.003) and β2M (p=0.03) at 24 h independently predicted CIN risk. β2M predicted increased mortality of 40% at baseline and 50% at 24 hours.  Median serum levels for 24 h cystatin C (β2M, and TNFα were best for predicting prognosis. Serum cystatin C at 24 h was the best biomarker for CIN diagnosis, while baseline levels of serum IL18,  Despite increased morbidity and mortality linked with iodinated contrast media-induced nephropathy (CIN) –4, earlyβ2M) are more sensitive early biomarkers of acute kidney injury (AKI) compared with serum creatinine [μmol/l) was linked with a 7-fold increased risk of mortality [Previous studies have demonstrated that neutrophil gelatinase lipocalin-2 (NGAL), cystatin C, interleukin 18 (IL18), kidney injury molecule 1 (KIM1), and beta-2 microglobulin  are upregulated in renal injury or damage [Cystatin C and ltration , 23, 24.ltration , 26, anded cells . NGAL, aed cells , 15, 28.r damage , 30 and r damage , 21, makβ2M, IL10, KIM1, and TNFα in predicting risk for CIN and their role in predicting patient outcomes.Previous studies on novel biomarkers focused on homogeneous populations characterised by nonheterogeneous AKI insults (surgery and nonmixed intensive care units), but few were based on radiocontrast studies. Our study investigated the diagnostic potential of NGAL, IL18, cystatin C, This nested case-controlled study was performed on a subset of patients undergoing contrast media administration at Charlotte Maxeke Johannesburg Academic Hospital, South Africa, from July 2014 to July 2015, who were followed up for development of CIN in a cohort of 371 patients . CIN wasα, NGAL, KIM1, and cystatin C were determined using Magnetic Luminex® Screening Assays  in accordance with the manufacturer's instructions on the BioPlex™ 200 system . The Bio-Plex manager software, version 5, was used for the determination of concentrations. Serum concentrations of β2M were determined by an enzyme-linked immunosorbent assay (ELISA) . Serum creatinine was determined using the Jaffe method.Whole blood and urine were collected at four time points: baseline (precontrast) and 24 hours, 48 hours, and 5 to 7 days after contrast administration. Blood and urine samples were centrifuged at 5000 rpm at 4°C for 10 and 2 minutes, respectively , and the sera and urine were stored at −80°C until assayed. Concentrations of IL10, IL18, TNFThe study outcomes were discrimination performance of the novel biomarkers for CIN at different time intervals and in-hospital CIN-associated mortality.p values of <0.05 were required for statistical significance.Data analyses were performed with Stata version 13 software . Biomarker characteristics were described as medians and interquartile ranges (IQRs) as values were not normally distributed. Urinary KIM1 levels were below detectable limits in 29% of samples analysed. For these samples, a proxy level of 12.2 pg/ml (the lower level of detection (17.3 pg/ml) divided by the square root of 2) was used. Comparisons of biomarkers with CIN and mortality were determined using the Wilcoxon–Mann–Whitney test. To determine discrimination performance of biomarkers for CIN vs. non-CIN and mortality , area under receiver operating characteristic curves (AUROCs) were constructed. Sensitivity and specificity were calculated for each point on the curve, and the optimal cutoff point was determined by finding the point with the maximum Youden index (Youden index = sensitivity + specificity − 1). Positive predictive values (PPVs) were calculated for the optimal cutoff point using the following formula: PPV = (number of true positives)/. Similarly, the negative predictive values (NPVs) were calculated for the optimal cutoff point using the following formula: NPV = (number of true negatives)/ . Multivariable regression analysis of biomarkers, adjusted for age and gender, were performed to determine predictors of CIN and mortality. β2M at all time points and baseline urine NGAL concentrations. Median serum cystatin C was also significantly increased at 24 and 48 h time points in the CIN group.This nested study included 30 CIN participants matched with 60 controls with a median age of 50 years (36–61). Participants' demographic characteristics are presented in β2M at 48 hours and baseline urine NGAL showed the best early discrimination performance for CIN diagnosis with AUROCs of 0.75, 0.78, and 0.74, respectively. Optimal cutoff values for biomarkers in predicting the development of CIN are shown in The ROCs for various biomarkers were generated for the determination of early CIN diagnosis Figures  and 2. Sβ2M showed superiority in excluding patients at risk of developing CIN (NPVs > 0.80). Cystatin C at baseline and at 24 hours showed the best predictive values for CIN. Multivariate analysis showed that, after adjusting for age and gender, levels of cystatin C and β2M at 24 hours showed significant odds ratio (OR = 1.00 (p=0.003) and OR = 1.26 (p=0.029), respectively) for predicting CIN development.Baseline serum levels of NGAL and p < 0.001), β2M (p=0.04), TNFα (p < 0.001), and baseline urine KIM1 (p=0.01) were elevated in the group who died. Twenty-four-hour urine NGAL (p=0.02) was also significantly increased in this group. Baseline and postcreatinine measurements were not statistically different between the surviving and nonsurviving groups. ROCs for biomarker discrimination performance for CIN mortality are shown in Figures α, IL18, and β2M showed best discrimination for CIN mortality with AUROCs of 0.94, 0.83, and 0.82, respectively. Multivariable regression analysis showed baseline and 24-hour β2M to have significant odds of predicting mortality (OR = 1.41 (p=0.01) and OR = 1.51 (p=0.003), respectively) after adjusting for other confounders.β2M p=0.0, TNFα  patients undergoing angiography, Briguori et al. observed nonsignificant differences between levels of cystatin C in the CIN group compared to controls at baseline . HoweverIn a meta-analysis that included 19 studies, Zhang et al. reported that 24-hour cystatin C measurements had the best discrimination for AKI in patients with homogeneous insults to the kidney, and measurements after 24 hours were better in patients with nonhomogeneous insults to the kidney . This meThere are several reasons why serum cystatin C demonstrates best discrimination for detecting early AKI, including CIN. Cystatin C is a filtration biomarker whose serum or plasma concentration correlates linearly with the glomerular filtration rate and therefore is better at detecting subclinical renal function . Cystatiβ2M demonstrated prediction for early diagnosis of CIN and were associated with increased mortality. Several studies on β2M have focused on populations with underlying CKD [β2M in AKI patients compared to controls; however, the levels of serum creatinine remained unchanged [β2M demonstrated superiority in detection of AKI with sensitivity and specificity of 98% and 80% vs. 46% and 53% for serum creatinine [β2M in the AKI group compared to controls despite insignificant changes in levels of serum creatinine [β2M was also superior in early detection of AKI with an AUROC of 0.80 vs. 0.63 for serum creatinine [2 [In our study cohort, increased levels of ying CKD . In a stnchanged , 38. Afteatinine . In anotβ2M levels were associated with increased mortality in our study. In previous reports among CKD patients who died, increased β2M was an independent predictor of mortality [β2M and mortality in our study cohort. Firstly, the predominant underlying comorbidity of our cohort was malignancy as found in previous studies; malignancy, together with microinflammation, was associated with increased secretion of β2M [β2M levels is heightened [β2M is a filtration biomarker produced by nucleated cells [Increased serum ortality , 40. Twoed cells , which ued cells , 27 and In our study, NGAL was a good predictor for patients at low risk for the development of CIN. This finding is supported by two recent studies limited to CIN: one conducted in Italy among patients with underlying renal disease who underwent angiography  and anotIn an additional study, patients undergoing contrast administration were characterised by various heterogeneous insults to the kidney  comparedα together with urine KIM1 demonstrated prognostic significance with mortality in CIN+ patients, despite the poor diagnostic discrimination performance for CIN. In a recent meta-analysis correlating urine IL18 with AKI, the diagnostic discrimination performance of IL18 was modest with an AUROC of 0.66 in adults [In our study, serum IL18 and TNFn adults  and was n adults . In a prn adults . Increasn adults . In a prn adults . KIM1 isn adults , similarn adults , 50, ourThe strength of this study is that it was a prospective case-controlled study that evaluated serum and urine biomarkers and also compared several biomarkers in discriminating CIN diagnosis and patient outcomes. Additionally, our study population was heterogeneous unlike previous homogeneous studies.The limitation of our study is that it was conducted at a single-centre tertiary hospital. An additional limitation was the inability to perform measurements within 2–6 hours after contrast administration which remained a challenge in our study cohort, and few patients in our study had intra-arterial contrast media administration unlike previous studies.β2M, and TNFα were best for predicting prognosis. However, more studies are needed to explore the impact of late biomarker measurements on CIN and mortality.In conclusion, novel biomarkers have better diagnostic discrimination for CIN and prediction of outcomes in patients with heterogeneous insults to the kidney. Serum cystatin C at 24 h was the best biomarker for CIN diagnosis, while baseline levels of serum IL18,


Porphyromonas gingivalis. The fact that neutrophils are the dominating cell type in the gingival pocket suggests that neutrophil-specific chemoattractants are released by subgingival bacteria, but characterization of chemoattractants released by subgingival biofilm species remains incomplete. In the present study we characterized small (< 3 kDa) soluble chemoattractants released by growing P. gingivalis, and show that these are selective for neutrophils. Most neutrophil chemoattractant receptors are expressed also by mononuclear phagocytes, the free fatty acid receptor 2 (FFAR2) being an exception. In agreement with the selective neutrophil recruitment, the chemotactic activity found in P. gingivalis supernatants was mediated in part by a mixture of short chain fatty acids (SCFAs) that are recognized by FFAR2, and other leukocytes (including monocytes) did not respond to SCFA stimulation. Although SCFAs, produced by bacterial fermentation of dietary fiber in the gut, has previously been shown to utilize FFAR2, our data demonstrate that the pronounced proteolytic metabolism employed by P. gingivalis  may result in the generation of SCFAs that attract neutrophils to the gingival pocket. This finding highlights the interaction between SCFAs and FFAR2 in the context of P. gingivalis colonization during periodontal disease, but may also have implications for other inflammatory pathologies involving proteolytic bacteria.Neutrophil migration from blood to tissue-residing microbes is governed by a series of chemoattractant gradients of both endogenous and microbial origin. Periodontal disease is characterized by neutrophil accumulation in the gingival pocket, recruited by the subgingival biofilm consisting mainly of gram-negative, anaerobic and proteolytic species such as  Porphyromonas gingivalis, is a gram negative, rod-shaped bacterium that is more frequently found in subgingival biofilms from patients with periodontitis, as compared to samples from healthy donors , debris should be cleared and, the resolution phase of the inflammatory reaction should be initiated . Accordi2+ concentration, which together with other downstream signaling events leads to directional migration (4) deliver neutrophils from the circulation to tissues, chemotactic factors released by bacteria or damaged host cells , or generated on bacterial surfaces (C5a) direct them into close contact with the microbes. Consequently, endogenous chemoattractants play an intermediate role in attracting neutrophils to the vicinity of infection, and bacteria-derived substances are thought to play central roles as end-point chemoattractants capable of guiding the phagocytes all the way to its prey (All neutrophil chemoattractant receptors are G-protein-coupled receptors (GPCRs), and one critical process triggered by ligation of many GPCRs is a transient increase in intracellular Caigration . Neutropits prey . While eits prey  and agonits prey , the shoits prey . The ideproteolytic bacterial metabolism and have in fact been demonstrated to form when oral anaerobes  utilize proteins as an energy source in vitro  are part of a larger group of free fatty acids that are present as intermediate metabolites in circulation and tissues . Free fain vitro . SCFAs ain vitro , and a nreceptor . In vivo colitis . Thus, iin vitro . Written informed consent was obtained from all individuals who donated peripheral blood. Buffy-coats from healthy donors were obtained from the blood bank at Sahlgrenska University Hospital. Since the buffy coats were provided anonymously and could not be traced back to a specific individual, ethics approval was not needed.2+ (1 mM) and kept on ice until use. For certain experiments, the total leukocyte content of buffy coats was used (separated as above but without Ficoll-Paque).Human neutrophils were isolated from buffy-coats or peripheral blood from healthy blood donors as first described by P. gingivalis (P16 (OMGS 711) and P24 (OMGS 766)) obtained from the strain collection at the department of Oral Microbiology University of Gothenburg, Sweden (OMGS) . For normalization of different supernatants, all bacterial suspensions were diluted to 1 × 1010 CFU/ml (based on OD550 nm), before centrifugation at 14000×g, for 5 min at 4°C. Supernatants were sterile-filtered through 0.2-μm filters (Corning), freeze-dried and stored at −80°C. Samples of supernatant were cultured to ascertain sterility. Supernatants from agar plates without bacteria, prepared in a similar manner as the bacterial supernatants, were used as negative controls.Two laboratory strains (W83 and 381), and two clinical isolates of n (OMGS) , were us2O  and centrifuged through size-exclusion filters  for 20 min at 14000×g and 4°C. This step was done to focus on small soluble chemoattractants and to remove LPS and other large bacterial products; endotoxin levels in the final supernatants were < 0.05 EU/ml as determined by limulous amoebocyte lysate test. All experiments shown are from size filtered supernatants prepared in this way.Before use, all freeze-dried supernatants were dissolved in dH6 cells/ml) from human peripheral blood samples were resuspended in KRG supplemented with Ca2+ and 0.3% bovine serum albumin (BSA), and loaded on a 3-μm polycarbonate chemotaxis membrane with hydrophobic mask . Cells (6 × 104 cells/well) were allowed to migrate over the membrane towards chemotactic stimuli; i.e., bacterial culture supernatants , SCFAs, fMLF (10 nM) or buffer for 90 min, 37°C, 5% CO2. Migrated cells were lysed with 2% cetyltrimethylammonium bromide in phosphate buffered saline (PBS) with 2% BSA, and quantified by measuring myeloperoxidase (MPO) activity in cell lysates with peroxidase reagent  in phosphate citrate buffer , according to manufacturer’s instructions. Absorbance at 450 nm was measured in a plate reader . Values were calculated as a percentage of the positive control (6 × 104 lysed cells). When migration was stimulated with SCFAs, pH was adjusted to be equal in all wells before MPO quantification.Isolated neutrophils  that express FPR1 and FPR2, respectively (The abilities of culture supernatants of the four ectively . The Pat2+ with 1% heat-inactivated FCS) at 1 × 107 cells/ml. Cells were loaded with Fluo-3 AM (3.6 µl/ml) and Fura-Red (10 µl/ml) and incubated for 30 min at 37°C, washed twice and resuspended in cell-loading medium at 6 × 106 cells/ml. Before analysis, cells were incubated for 5 min at 37°C  for 20 min, at 4°C. CD45 is differentially expressed on distinct leukocyte subsets and facilitate the gating on neutrophils, monocytes and lymphocytes. The cell types  were gated based on CD45 and side scatter properties and the Caparately .2+ with 1% DMSO (Sigma).To separate hydrophobic and hydrophilic molecules, the size sorted (< 3 kDa) bacterial supernatants were passed through a C18 solid phase extraction (SPE) cartridge , according to manufacturer’s instructions. Unbound flow through, containing the hydrophilic fraction, was collected and stored at -20°C. Retained molecules were eluted from the C18 column using 40% (V/V) acetonitrile containing 0.05% (V/V) formic acid, dried and resuspended in KRG supplemented with CaP. gingivalis culture supernatant, 10 μl methanol (75%), 10 μl 200 mM 3-NPH (3-nitrophenylhydrazine in MeOH (75%)), 10 μl 120 mM EDC-6% pyridine (N-(3-Dimethylaminopropyl)-N-ethylcarbidiimide in 75% MeOH with 6% pyridine) was mixed and incubated 45 min, RT with shaking. The derivatization reaction was quenched with 10 μl of 200 mM quinic acid in MeOH, mixed and incubated 15 min, RT with shaking. 950 μl of water was added to the samples followed by centrifugation at 15,000×g, RT, for 5 min. 100 μl of supernatant and 100 μl of internal standard (13-C 3-nitrophenylhydrazine labeled short chain fatty acids) transferred to HPLC vials. Samples were analyzed immediately or kept at 4°C until analysis.Sample derivatization: 10 µl of The samples were analyzed with LC-MS/MS consisting of an ExionLC UHPLC system coupled to a 6500+ QTRAP . The analytes were separated in a Phenomenex Kinetex C18  column, at 40°C, following gradient: 0–3 min 0.5% B, 3.00–3.01 min 0.5–2.5% B, 3.01–6.00 min 2.5–17% B, 6.00–10.00 min 17–45% B and 10.00–13.00 min 45–55% B, followed by washing and re-equilibration of the column. Mobile phase A and B were water and acetonitrile, respectively, and total flow was set to 0.4 mL/min. APCI ionization was used in positive polarity and the analytes were detected using optimized MRM-transitions for each analyte and internal standard. A calibration curve covering the range of the analytes in the samples was injected together with the analytes.p-value less than 0.05 was considered statistically significant and level of significance is indicated in the figures: ns >0.05, *< 0.05, **< 0.01, ***< 0.001. The statistical tests used are specified in the figure legends.Non-parametric statistical tests were used to determine significance. All statistical analyses were performed in GraphPad Prism software . A The work was supported by the Swedish Research Council , the Swedish Foundation for Strategic Research , and the Swedish state under the ALF-agreement  and TUA-agreement . The sponsors did not have any role in any part of the study.P. gingivalis were able to induce neutrophil chemotaxis in vitro. Supernatants from bacterial cultures, in three different dilutions , were used as chemotactic stimuli and the potent neutrophil chemoattractant fMLF was used as a positive control. Supernatants prepared from cultures of all four strains induced neutrophil chemotaxis in a dose-dependent manner  soluble factors derived from two established lab strains (W83 and 381), and two clinical isolates (P16 and P24) of 2+ in the cytoplasm  induced no measurable FPR1 activation, and the two clinical isolates (P24 and P16) induced very low levels of FPR1 activation  and released by a number of different bacteria , we testS. salivarius supernatant, neither of the P. gingivalis supernatants induced measurable FPR2 activation  (Formyl peptide receptor 2 (FPR2) is a related receptor to FPR1 and structurally very similar, sharing 69% of protein sequence . While fes (ROS) .P. gingivalis (strain 381) supernatant based on hydrophobicity using C18 reversed phase SPE cartridges. Whereas hydrophilic molecules pass through the C18 cartridge and are collected as the flow through fraction (FT), hydrophobic components are retained and later eluted (EL fraction) using an organic solvent. The two fractions of the P. gingivalis supernatant (FT and EL) were then used to stimulate intracellular Ca2+ signaling and chemotaxis in neutrophils. All activity, both Ca2+ signaling , where all Ca2+ signaling activity was recovered in the EL fraction. This fits well with the absence of FPR activation in P. gingivalis supernatants  with the same composition and at concentrations similar to those found in the culture supernatants of GLPG0974 . Ca2+ re2+ signals induced by the hydrophilic fraction (FT) from P. gingivalis supernatants  .We stimulated mixed leukocyte samples with fMLF, C5a, SCFAs, or esponses . By gatiP. gingivalis  contained soluble bacterial products that stimulate neutrophil chemotaxis in vitro. One of our previous studies showed that neutrophil intracellular Ca2+ signals can be triggered by stimulation with a supernatant derived from a cultured periodontitis bacterial sample, which along with directional migration, is a characteristic neutrophil response to ligation of chemotactic GPCRs   , and wournatants , and theP. gingivalis contained micromolar concentrations of acetic acid (29.8–108.1 µM), propanoic acid (7.5–27.5 µM), butyric acid (24.9–97.4 µM), iso-butyric acid (3.5–16.8 µM), succinic acid (17.5–24.5 µM) and iso-valeric acid (8.2–32.7 µM). There are earlier reports on millimolar concentrations of acetic acid, butyric acid, propionic acid, iso-butyric acid and iso-valeric acid in culture supernatants of P. gingivalis  or an allosteric FFAR2 modulator respectively confirmed that the SCFA triggered Ca2+ signals were indeed mediated via FFAR2. This is in coherence with earlier studies showing FFAR2 dependent Ca2+ signaling after stimulation with the individual SCFAs; acetic acid, propanoic acid, and butyric acid   FFAR2 indicate that SCFAs released by P. gingivalis could be one important factor that contribute to neutrophil specific chemotaxis into the gingival pocket.It is well established that neutrophils are the most abundant leukocytes in GCF (80–98% of leukocytes) , which cP. gingivalis release a mixture of SCFAs that induces FFAR2 mediated intracellular Ca2+ signals and chemotaxis in human neutrophils. The functional effects of SCFAs also proved to be neutrophil specific, which further strengthen their role as important chemoattractants in the interplay between periodontal microbes and host defense. Furthermore, as the proteolytic metabolism generating SCFAs is a common trait of the anaerobic bacterial species that colonize the deep periodontal pocket, our finding could also apply to other oral anaerobes as well as other inflammatory pathologies driven by colonization/infection by proteolytic bacteria.In the present study, we show that The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.ADR, OS, HF, CD, KC, and JB participated in research design. Experiments were conducted by ADR, AK, TP, and OS. Results were analyzed by ADR, AK, VV, TP, MG, KC, and JB. ADR and JB wrote the paper, which was critically revised by all authors. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Brassicogethes aeneus, a key pest of oilseed rape (Brassica napus) in Europe, is greatly needed. Gene silencing via RNA interference, through sprayed applications of target-specific double-stranded RNA, represents a potential alternative to conventional insecticides. We used dsRNA designed to target a vital gene in this pollen beetle species and allowed the beetles to feed on dsRNA-coated oilseed rape buds. We observed a significant silencing of the target gene; and this was followed by a significant, albeit delayed, reduction in pollen beetle survival rate. Further experiments are necessary in order to better understand the potential for developing a dsRNA-spray approach to pollen beetle management.An ecologically sustainable strategy for managing the pollen beetle Brassicogethes aeneus) management in oilseed rape (Brassica napus) agroecosystems is needed. We examined the potential for SIGS in B. aeneus, via bud feeding, a field-relevant dsRNA exposure route. Oilseed rape buds were uniformly treated with dsRNA designed to target αCOP in B. aeneus. Our model control dsRNA (dsGFP) remained detectable on buds throughout the entire 3 d exposure period. When applied at 5 µg/µL, dsαCOP induced significant αCOP silencing 3 d after dietary exposure to buds treated with this dsαCOP concentration. We also observed a trend of increased αCOP silencing with increasing concentrations of dsαCOP at both 3 and 6 d. Furthermore, we observed a marginally significant and significant reduction in B. aeneus survival at 10 and 15 d, respectively. Our results suggest potential for developing a SIGS approach to B. aeneus management—though further experiments are needed to more fully understand this potential.Spray-induced gene silencing (SIGS) is a potential strategy for agricultural pest management, whereby nucleotide sequence-specific double-stranded RNA (dsRNA) can be sprayed onto a crop; the desired effect being a consumption of dsRNA by the target pest, and subsequent gene silencing-induced mortality. Nucleotide sequence-specificity is the basis for dsRNA’s perceived biosafety. A biosafe approach to pollen beetle ( Brassicogethes aeneus Fab. (syn. Meligethes aeneus) is a key pest of oilseed rape (Brassica napus L.) in Europe. Adult B. aeneus overwinter in soil, under vegetation and leaf litter; they emerge in early spring to feed on the pollen and nectar of a variety of blooming plants, and subsequently colonize brassicaceous plants, where they obtain nutrients from reproductive buds and open flowers. After mating, females oviposit into buds, and upon hatching, larvae feed on anthers within buds, eat their way out of the buds, and feed in open flowers, eventually pupating under the soil surrounding the host plant . Oilseeion time ,3. Curreacloprid ,5. Theseacloprid ,7,8, a fulations ,10.B. aeneus management is needed. One biosafe approach to B. aeneus management is via conservation biocontrol, where habitats and habitat features required by the parasitoids of B. aeneus are preserved or restored in oilseed rape agroecosystems, ideally at both local and regional scales [To achieve ecologically sustainable oilseed rape production, an integrated and biosafe scheme for l scales ,12,13,14Leptinotarsa decemlineata Say). In contrast to host-induced gene silencing (HIGS) via the use of an RNAi cultivar, a SIGS approach has the benefit of not requiring the biotechnology or time required for engineering an RNAi cultivar.Gene silencing via RNA interference (RNAi) represents a potential approach to utilize within integrated pest management . As RNAiαCOP), encoding the αCOP protein, and showed RNAi efficacy in B. aeneus via honeywater feeding , indicating potential for RNAi-based control of B. aeneus via dsRNA-contaminated nectar. However, B. aeneus also requires the lipid and protein constituents of pollen, which they consume from both buds and open flowers. As mentioned above, the most vulnerable stage of oilseed rape growth, with respect to B. aeneus, is the green bud stage; as this is the time when B. aeneus females oviposit within buds, and both male and female adult B. aeneus feed on pollen within buds in order to acquire lipid and protein constituents. Therefore, it is critical to examine RNAi efficacy via bud feeding in B. aeneus.We recently targeted the vital gene coatomer subunit alpha   and αCOP (our target gene). The dsRNAs are hereafter referred to as dsGFP and dsαCOP. The absence of nucleic contaminants in dsRNA products was determined via gel electrophoresis.A selected 222 bp region from in (gfp) , were thB. aeneus prior to their use in this study. Winter oilseed rape plants were kept in a 3 × 3 m climate room  at 10 °C (70 ± 5% relative humidity and 16:8 h light:dark cycle), in order to maintain them at a low growth stage. Before starting the experiment, the temperature in the climate room was increased to 18 °C. Pollen beetles and oilseed rape plants (BBCH 31−32) were both collected from untreated organic oilseed rape fields  in the respective villages of Õssu and Nasja, Tartu County, Estonia. Beetles were kept in ventilated plastic containers, allowed to feed ad libitum on the pollen of oilseed rape flowers, and identified as B. aeneus were released within a transparent-white organza fabric bag (20 × 30 cm) that was fastened with string to the neck of the labware. The beetles were allowed to feed ad libitum on the treated buds for 3 d. The 3 d exposure to the dsRNA-treated bud took place in the climate room at 18 °C, 70 ± 5% relative humidity and 16:8 h light:dark cycle.Leading racemes, ranging 18‒24 cm in length, were removed from oilseed rape plants during the green bud stage (BBCH 53‒55). Treatments were prepared from dsRNA, dH2O and a constant concentration (180 ppm) of the surfactant Triton X-100 (Fisher Bioreagents) and were vortexed prior to soaking bud clusters. There were three treatments in total, including dsGFP at 5 µg/µL, and dsαCOP at 2.5 and 5 µg/µL. Bud clusters were swirled in treatment solutions for 1 min (this action and duration were both required in order to reliably break the surface tension caused by the waxiness of the bud epithelium), and subsequently allowed to air dry for 1 h. The cut tip of each raceme was then kept underwater, individually, in modified plastic labware (height 12 cm). For each sample, six For each experimental replicate, each treatment was initially allocated five samples; and the experiment was replicated three times. Beetles were not disturbed during their 3 d exposure to dsRNA treatments; thus, survival monitoring began after the 3 d exposure period, and thereafter occurred every 24 ± 1 h. After 3 d of feeding on treated buds, bud-feeding setups were dismantled, and the beetles were transferred to transparent, polystyrene, ventilated insect breeding dishes (diameter 10 cm × height 4 cm) , hereafter referred to as cages; and the beetles were kept in their respective samples. After this relocation to the laboratory, the beetles were maintained in an incubator  and provisioned daily with fresh untreated oilseed rape flowers, and a dental cotton roll soaked with dH2O. Survival monitoring for each experimental replicate lasted 15 d post-exposure to dsRNA. Escaped beetles were accounted for in the statistical analysis, and any sample where more than two beetles escaped were removed from the analysis at the start of survival monitoring (n = 14 (83 beetles), 14 (80 beetles) 15 (87 beetles), for dsGFP at 5 µg/µL, dsαCOP at 2.5 µg/µL and dsαCOP at 5 µg/µL, respectively). ribosomal protein S3 (rps3) and actin (act) were used to normalize the data. Primer amplification efficiencies were determined via a cDNA dilution series. Primer sequences and amplification efficiencies are shown in ‒ΔΔCt method. A no-template control and a no reverse transcriptase control were included in the assay.Relative gene expression analysis was performed for all treatments via quantitative polymerase chain reaction (qPCR). For each experimental replicate, at 3 d (upon dismantling the bud-feeding setups), and again 6 d after the start of bud feeding, one cage of six live beetles was randomly removed from each treatment (qPCR sample n = 3 per treatment). The removal of beetles for qPCR was accounted for in the statistical analysis. Beetles used for qPCR were immediately placed in their respective Eppendorf tubes and homogenized using a sterilized plastic pestle designed for Eppendorf tubes, in 600 µL of RLT buffer (with added 10 µL of β-mercaptoethanol), and stored at −80 °C until analysis. Total RNA was extracted using an RNeasy Mini Kit ; and RNA concentration and purity were assessed using a nanodrop spectrophotometer , with purity further verified via gel electrophoresis. Genomic DNA was removed using a Turbo DNA-Free Kit , following manufacturer’s instructions. The cDNA was reverse transcribed from 1 µg of total RNA using a FIREScript RT cDNA Synthesis Kit ; and qPCR was performed in the Quantistudio 5 Real-Time PCR System . The reaction included 4 µL of 5xHOT FIREPol EvaGreen qPCR Supermix , 0.5 µL of both 10 µM forward and reverse primers , following the manufacturer’s protocol; and RNA concentration was quantified, and purity assessed, using a nanodrop spectrophotometer , with purity further verified via gel electrophoresis. The detection of dsGFP was performed from 500 ng of RNA, using a SuperScript III One-Step RT-PCR System  with gfp-specific primers at 10 pmol . Both 20Regarding both survival- and gene expression analysis, comparisons were made between dsGFP and both concentrations of dsαCOP, and between the two concentrations of dsαCOP. For survival analysis, the homogeneity of variance and normality of data distributions were determined using the Levene and Shapiro–Wilk tests, respectively. Since the data were overall not normally distributed, the Kruskal–Wallis test was used as a nonparametric alternative to ANOVA; this was followed by the Wilcoxon rank-sums test, with Bonferroni correction, for post hoc pairwise comparisons. For gene expression analysis, comparisons were made using Welch’s t-test. All statistical analyses were done in R v3.6.3 .p = 0.3), and a 72% mean decrease in the dsαCOP 5 µg/µL treatment . At 6 d, we observed a 19% mean decrease in αCOP expression in the dsαCOP 2.5 µg/µL treatment , and a 48% mean decrease in the dsαCOP 5 µg/µL treatment .RT-PCR results confirmed the presence and stability of dsRNA on buds, over the entire 3 d of exposure to treatments, for both dsGFP concentrations examined . In the p = 0.02; 15 d: chi-square = 10.38, df = 2, p = 0.006; p = 0.056), becoming significant at 15 d (p = 0.021). Survival in this treatment slowly fell from 100% (4 d) to 99 (5 d), 97 (6 d), 96 (7 d), 94 (8 d), 92 (9 d), 88 (10 d) and 84% (15 d). No significant effect on survival was observed for the dsαCOP 2.5 µg/µL treatment, survival falling from 100% (7 d) to 98% (8 d), where it settled. No mortality was observed in the dsGFP treatment. After the 3 d treatment–exposure period, all bud clusters had numerous buds incised, with both anthers and bud epithelium consumed. Together with the fact that all caged beetles survived over the entire 3 d treatment–exposure period, which indicates that all beetles fed on dsRNA-treated bud tissue.Regarding survival, we began observing a significant effect of treatment at 10 d  insecticides, there are great benefits to using dsRNA-based insecticides due to the associated biosafety to nontarget organisms, stemming from its unique mode of action. Moreover, there remains potential for increasing speed-to-effect via co-formulants  that may improve dsRNA-uptake and RNAi efficiency ,21. ImprB. aeneus. While our work suggests potential for developing a SIGS approach for implementation in B. aeneus management, further experiments are needed to more fully explore the potential for incorporating this approach. Focal points necessary for progress here include determining the potential for enhancing adult B. aeneus control efficacy, and that of both larval and adult B. aeneus simultaneously, via the use of co-formulants to enhance the transport of dsRNA to anthers within oilseed rape buds. Other important focus points include determining the total duration at which exogenously-applied dsRNA remains viable both on- and within the reproductive bud; and determining the optimal duration of exposure to dsRNA-treated buds, taking into account the time-to-flowering of buds. Finally, it will be critical to determine the overall feasibility of using a SIGS approach in the context of a potential requirement for successive dsRNA spray applications.Ecologically sustainable control measures are greatly needed in oilseed rape production; and dsRNA-based insecticides, due to their mode of action, represent a potentially species-specific complement to other biosafe measures  for managing


There is evidence to consider that the tumor microenvironment (TME) composition associates with antitumor immune response, and may predict the outcome of various non-Hodgkin lymphoma subtypes. However, in the case of mantle cell lymphoma (MCL), a rare and aggressive disease, there is lacking a detailed study of the TME components, as well as an integrative approach among them in patients’ samples. Also, from the genetic point of view, it is known that single nucleotide variants (SNVs) in immune-response genes are among important regulators of immunity. At present, it is uncertain whether SNVs in candidate immune-response genes and the TME composition are able to alter the prognosis in MCL.IL12A, IL2, IL10, TGFB1, TGFBR1, TGFBR2, IL17A, IL17F) in 95 MCL patients. We tested whether the SNVs could modulate the respective protein expression and TME composition in the tumor compartment. Finally, we proposed survival models in rituximab-treated patients, considering immunohistochemical and SNV models.We assessed a detailed TME composition in 88 MCL biopsies using immunohistochemistry, which was automatically analyzed by pixel counting (Aperio system). We also genotyped SNVs located in candidate immune-response genes (p = 0.001), high IL17A levels (p = 0.003) and low IL2 levels (p = 0.03) were individual immunohistochemical predictors of poorer survival. A principal component, comprising high quantities of macrophages and high Ki-67 index, also worsened outcome (p = 0.02). In the SNV model, the CC haplotype of IL10 (p < 0.01), the GG genotype of IL2 rs2069762 (p = 0.02) and the AA+AG genotypes of TGFBR2 rs3087465 (p < 0.01) were independent predictors of outcome. Finally, the GG genotype of TGFB1 rs6957 associated with lower tumor TGFβ levels (p = 0.03) and less CD163+ macrophages (p = 0.01), but did not modulate patients’ survival.High FOXP3/CD3 ratios (IL10, TGFBR2 and IL2, may represent novel prognostic factors in this disease, following future validations.Our results indicate that the TME composition has relevant biological roles in MCL. In this setting, immunohistochemical detection of T-reg cells, IL17A and IL2, coupled with SNV genotyping in The online version contains supplementary material available at 10.1186/s12885-021-07891-9. TP53 / CDKN2A mutations, were associated with treatment resistance [Mantle cell lymphoma (MCL) is an uncommon non-Hodgkin lymphoma (NHL) subtype, marked by presence of the t 11:14) translocation in more than 90% of the cases, which leads to overexpression of cyclin D1 1:14 tran. More reIn this setting, the composition of tumor microenvironment (TME) has emerged as a promising prognostic marker in patients with a variety of tumors, including NHLs . The TMEHowever, as the capacity of immune response is variable in humans , it may Herein, we assessed the prognostic role of immune-response components of the TME in biopsies from a retrospective cohort of MCL. We also studied SNVs in immune-response related genes, attempting to elucidate whether they could alter the TME composition and the outcome of MCL patients.n = 74) and A. C. Camargo Cancer Center (n = 48).We analyzed all 122 MCL cases diagnosed between 1999 and 2016 at the Hematology and Hemotherapy Center of the University of Campinas  Classification for Lymphoid Tumors . Tumor cIL12A, IL2, IL10, TGFB1, TGFBR1, TGFBR2, IL17A and IL17F  and purity (260/280 and 260/230 ratios) were performed using the NanoDrop spectrophotometer . Whenever necessary, sodium acetate (3 M) was added to the extracted DNAs, followed by new ethanol precipitations, to improve purity. The final concentration of all samples was set to 50 ng/μL.Genotyping of SNVs was performed using the Taqman® OpenArray® QuantStudio™ Real-Time PCR System . Briefly, DNA samples were pipetted together with Taqman® Openarray® Master Mix on 384-well plates. This mixture was then transferred to genotyping plates using the Openarray® Accufill™ system. Thermocycling was performed during 40 cycles, and visualization of polymorphic alleles was possible by using fluorophores (VIC™ and FAM™). A single reaction allowed the simultaneous detection of all 16 SNVs.Formalin-fixed, paraffin embedded (FFPE) diagnostic blocks from MCL cases were obtained from the participating hospitals. All slides were reviewed by an experienced hematopathologist (JV), and two representative areas from each source block were selected to construct a tissue microarray (TMA). Core fragments with diameter of 1 mm were taken using a Tissue Microarrayer , and samples were put as duplicates in the recipient block. Immunohistochemistry was then performed, using a broad panel of antibodies to study key TME components, including tumor-infiltrating lymphocytes  and macrophages . We also performed immunohistochemistry to detect the proteins encoded by the genes used in the SNV approach . Reactions for Ki-67 and SOX11 were performed as well. A detailed list of antibodies, including suppliers and dilutions, is in supplementary Table Eighty-nine blocks were used for SOX11 evaluation, and 88 were considered suitable for TME assessment.The immunohistochemical (IHC) reaction was performed using standard procedures. Briefly, unstained slides were submitted to antigen retrieval using citric acid solution/pH 6.0 or EDTA/pH 9.0 buffers. Endogenous peroxidase activity was blocked by hydrogen peroxide solution for 20 min. Exposure to the primary antibody was performed overnight. The signal was amplified by a third generation polymer tagged with anti-mouse/anti-rabbit immunoglobulins and horseradish peroxidase , and the color was developed with diaminobenzidine chromogenic substrate . Positive cells were observed in golden brown color. The negative control was performed by omitting the primary antibody.Quantification of IHC markers was performed on the entire TMA cores. For the majority of the markers, this was done automatically using the Aperio ImageScope™ software  Fig. . The Poshigh (nuclear staining in more than 10% of cells) or SOX11low (nuclear staining in less than 10% of cells or negative staining).For SOX11 assessment, we performed categorization using a visual approach, similarly to others , 45. In Immunohistochemical scores were analyzed individually and also as part of a dimension-reducing methodology .Associations between variables were assessed using χ2, Fisher’s exact test, Mann Whitney’s test and Spearman’s correlation index. When necessary, continuous variables were dichotomized as “high” and “low” based on the median values.www.broad.mit.edu/mpg/ haploview) to ensure that the markers were appropriate for inclusion in the haplotype estimates. The LD was measured by the disequilibrium coefficient (D′), and LD significance was considered at a D′ ≥ 80%.Regarding SNVs assessment, the Hardy-Weinberg equilibrium (HWE) was evaluated using the chi-square (χ2) goodness-of-fit test. Pairwise linkage disequilibrium (LD) analyses were performed using the Haploview 4.2 software  with Varimax rotation was used as a dimension-reducing method in IHC quantifications. Interactions between IHC variables were estimated and expressed as principal components. In this setting, stronger interactions had higher computed variance values . The assp value of less than 0.10 in the univariate analysis. Simultaneous testing of redundant information (e.g. age and the MIPI) was not performed. Follow-up update was performed on January, 2019.Survival analyses were also performed. However, as anti-CD20 therapy may be a potential confounder for the TME function, only patients who received rituximab in first-line regimens were included in this analysis . In a siThe significant results of multivariate Cox regressions were internally validated using the Bootstrap resampling method (1000 replications).p value of less than 0.05 was considered statistically significant.When necessary, the Benjamini-Hochberg method was performed for correction of multiple comparisons. All statistical tests were two-tailed, and a Median age at diagnosis for all MCL patients was of 66 years old (range: 31–93), and there was a predominance of male sex (93/122 or 76.2%). The majority of patients (107/122 or 87.7%) were included in Ann Arbor stages III or IV. The MIPI allowed classification of available patients as high-risk disease (35.3%), followed by intermediate risk (27.0%) and, finally, low risk (24.6%). Seventy-eight patients (63.9%) had received rituximab as first-line therapy. Twenty-seven patients (22.1%) underwent hematopoietic stem-cell transplantation . The main clinical variables are detailed in supplementary Table In 88/122 (72.1%) cases, diagnostic FFPE blocks were suitable for TME assessment. The most frequent immune cells found on the MCL biopsies were T lymphocytes, mainly CD4+ . Macrophages (CD68+) were slightly less frequent . Regarding inflammatory cytokines, IL17A had the highest expression  , perforin with CD8 (p = 0.02), and CD68 with CD4 (p < 0.001), CD8 (p = 0.001), and IL10 (p < 0.001). IL17A and CD57 were inversely correlated (p = 0.008)  Fig. .Fig. 3Cp = 0.04). Also, higher levels of macrophages (CD68+) and higher CD4/CD8 ratios were found in patients with less aggressive MIPI categories . In contrast, higher CD8/CD3 ratios were more frequently found on high-risk MIPI patients (p = 0.02). Finally, high IL12A and IL17A levels associated, respectively, with bone marrow infiltration (p = 0.01) and blastoid cytology (p = 0.04) . The remaining cases (13/89 or 14.6%) were classified as SOX11low ; no other clinicopathological differences were seen  the HWE was observed , bone marrow infiltration (OS only) and MIPI index   and high CD8/CD3 ratios (p = 0.03) associated only with worse EFS, and low granzyme B levels presented a trend of association with worse EFS (p = 0.06)   Fig. a. High F6) Figs. b-d. On tIL2 rs2069762 negatively affected both EFS  and the TC + CC genotypes of IL17F rs763780 (p = 0.03) associated only with worse EFS  and low IL2 tumor levels  remained independent predictors of worse EFS, whereas high IL17A tumor levels were independently associated with worse OS   and prolonged OS . In addition, the GG genotype of IL2 rs2069762 remained an independent predictor of EFS . Finally, the AA+AG genotypes of TGFBR2 rs3087465 were associated with worse EFS .In the multivariate SNV model, presence of the CC haplotype in To address the interplay among TME components with a more biologically plausible approach, we used PCA to verify interactions and trends of convergence among the various IHC markers. The final PCA model was based on 6 factors and explained 75.02% of the variance . No other associations with features at diagnosis were seen.The presence of the fourth principal component was associated with blastoid cytology, using a linear regression model . After multivariate analysis, only the presence of the fourth component was significantly associated with worse OS  , who found that the predominance of CD4+ lymphocytes over CD8+ lymphocytes was associated with less aggressive disease . ComplemWhen evaluating the TME by PCA, tumors rich in CD163 and with a high proliferative index had a worse prognosis. An association with the blastoid cytomorphology was also observed. The presence of higher Ki-67 is a known prognostic factor in MCL , and a hIL10  was a predictor of better OS and EFS in MCL. In previous reports addressing patients with Hodgkin’s lymphoma and B-cell lymphomas, similar results were achieved for the second SNV individually [Regarding the genetic counterpart of the TME, we found that the CC haplotype in vidually , 57. It vidually . On the vidually  reportedvidually .TGFB superfamily were up-regulated in MCL samples, compared to controls, but this was little explored in further studies [TGFBR2 rs3087465 independently associated with poorer EFS. To the best of our knowledge, this is the first association of this SNV with survival in cancer patients. The” A” allele of rs3087465 was previously found to increase the promoter activity of TGFBR2 [TGFB1 rs6957 was not a predictor of outcome after multivariate analysis; however, the GG genotype was associated with decreased levels of TGFβ and CD163+ macrophages in MCL biopsies. These findings are similar to a previous report in asthma patients, in whom this SNV also modulated macrophage proliferation [Another potentially targetable pathway in MCL is TGFβ and related proteins. Rizzatti et al. (2005) described that several genes from the  studies . In our f TGFBR2 , but itsferation . HoweverIL2 rs2069762 was an independent predictor of worse EFS. This mirrors the findings of Cerhan et al. (2007), in which the same genotype worsened the survival of follicular lymphoma patients in the pre-rituximab era [Finally, considering the cytotoxic (Th1) immune-response pathway, we found that the GG genotype of imab era . Interesimab era . Even thimab era . TherefoIn our cohort of MCL, SOX11 expression was not associated with prognosis. The importance of this transcription factor for the diagnosis of MCL is already established . More reTP53 mutational status, which is a well-known prognostic factor in MCL [The limited sample size represents a drawback of this study. Furthermore, the two institutions involved in our study present different sociodemographical profiles that might influence response to therapy . In addir in MCL . Therefor in MCL .TGFBR2 rs3087465, IL2 rs2069762 and the CC haplotype of IL10. The distinct approach presented herein might contribute to novel insights in the biology of MCL, and in future studies considering new therapeutic options in this lymphoma.This is the first study to provide a broader approach of the TME in MCL, by evaluating both the TME immune cell composition in biopsies and SNVs within immune-response genes. Our study supports the associations of tumor FOXP3/CD3 ratios, IL17A and IL2 with outcome in the rituximab era. We also demonstrate, in the same cohort, the prognostic roles of Additional file 1: Supplementary Table 1. Primary antibodies used for immunohistochemistry in this study.Additional file 2: Supplementary Table 2. Clinicopathological features of the mantle cell lymphoma patients in this study.Additional file 3: Supplementary Table 3. Cellular microenvironment composition and clinicopathological features of mantle cell lymphoma.Additional file 4: Supplementary Table 4. Intratumoral expression of cytokines and clinicopathological features of mantle cell lymphoma.Additional file 5: Supplementary Table 5. SOX11 expression and clinicopathological features in mantle cell lymphoma.Additional file 6: Supplementary Table 6. Hardy-Weinberg equilibrium testing for all the SNVs assessed in this study.Additional file 7: Supplementary Table 7. Frequencies of haplotypes in IL10 and IL12A in mantle cell lymphoma patients.Additional file 8: Supplementary Table 8. Univariate Cox regression for clinicopathological features influencing survival of mantle cell lymphoma patients.Additional file 9: Supplementary Table 9. Principal component analysis of the immunohistochemical variables in mantle cell lymphoma.Additional file 10: Supplementary Fig. 1. Representative photomicrographs of tumor-infiltrating lymphocytes in mantle cell lymphoma. (A) CD3, (B) CD4, (C) CD8, (D) CD57, (E) FOXP3, (F) PD1, (G) Granzyme B, (H) Perforin. Each letter is sub-labeled as “1”, “2” and “3”, representing, respectively, cases with weak, intermediate and strong positivity. All images were obtained at a 200x magnification.Additional file 11: Supplementary Fig. 2. Representative photomicrographs of macrophages, iNOS staining and the proliferative index in mantle cell lymphoma. (A) CD68, (B) CD163, (C) iNOS, (D) Ki67. Each letter is sub-labeled as “1”, “2” and “3”, representing, respectively, cases with weak, intermediate and strong positivity. All images were obtained at a 200x magnification.Additional file 12: Supplementary Fig. 3. Representative photomicrographs of cytokines’ stainings in mantle cell lymphoma. (A) IL12A, (B) IL2, (C) IL10, (D) TGFβ, (E) TGFBR1, (F) TGFBR2, (G) IL17A, (H) IL17F. Each letter is sub-labeled as “1″, “2″ and “3″, representing, respectively, cases with weak, intermediate and strong positivity. The exception is for TGFBR2, in which no convincing positivity was observed; therefore, F1, F2 and F3 represent negative cases. All images were obtained at a 200x magnification.Additional file 13: Supplementary Fig. 4. Representative photomicrographs of SOX11 assessment in mantle cell lymphoma. (A)SOX11high case. (B)SOX11low case.Additional file 14: Supplementary Fig. 5. Tumor microenvironment markers (A-R) and proliferation index (S) in SOX11high and SOX11low mantle cell lymphoma cases. Horizontal lines represent the median levels, and the whiskers show interquartile ranges.Additional file 15: Supplementary Fig. 6. Linkage disequilibrium (LD) plots in mantle cell lymphoma patients for (A)IL12A and (B)IL10 genes. In each square, the LD is measured between groups of single nucleotide variants. Higher values of LD (expressed as D′) are shown in red squares.