Bacillus subtilis, Candida utilis, and cell-free extracts from Aspergillus oryzae were used to degrade ZEA in this study. The orthogonal experiment in vitro showed that the ZEA degradation rate was 92.27% (p < 0.05) under the conditions that Candida utilis, Bacillus subtilis SP1, and Bacillus subtilis SP2 were mixed together at 0.5%, 1.0%, and 1.0%. When cell-free extracts from Aspergillus oryzae were combined with the above probiotics at a ratio of 2:1 to make mycotoxin-biodegradation preparation (MBP), the ZEA degradation rate reached 95.15% (p < 0.05). In order to further investigate the MBP effect on relieving the negative impact of ZEA for pig production performance, 120 young pigs were randomly divided into 5 groups, with 3 replicates in each group and 8 pigs for each replicate. Group A was given the basal diet with 86.19 μg/kg ZEA; group B contained 300 μg/kg ZEA without MBP addition; and groups C, D, and E contained 300 μg/kg ZEA added with 0.05%, 0.10%, and 0.15% MBP, respectively. The results showed that MBP addition was able to keep gut microbiota stable. ZEA concentrations in jejunal contents in groups A and D were 89.47% and 80.07% lower than that in group B (p < 0.05), indicating that MBP was effective in ZEA biodegradation. In addition, MBP had no significant effect on pig growth, nutrient digestibility, and the relative mRNA abundance of estrogen receptor alpha (ERα) genes in ovaries and the uterus (p > 0.05).In order to remove zearalenone (ZEA) detriment— Fusarium species to cause reproduction disorders in female animals such as abortion, false estrus, and so on [Zearalenone (ZEA) is one of the nonsteroidal estrogenic mycotoxins produced by nd so on . Some ofnd so on ,3. Long-nd so on . Howevernd so on . In sorgnd so on . It was nd so on ,8,9. Anond so on . GeneralIn order to reduce ZEA detriment, many countries and organizations in the world have limited the maximal ZEA contents in food, feed, and cereals. For example, Australia allows a maximal ZEA content of 50 μg/Kg in cereals. ZEA content in cereals and cereal products is not allowed to exceed 100 μg/Kg in Italy. The maximal ZEA content in vegetable oil and cereals is 200 μg/Kg in France . The maxSaccharomyces cerevisiae [Bacillus subtilis (B. subtilis) ANSB01G [Lactobacillus plantarum [B. subtilis SP1, B. subtilis SP2, Candida utilis (C. utilis), and cell-free extracts of Aspergillus oryzae (A. oryzae) were selected and combined together to determine the effect on ZEA detoxification and pig production performance, which will supply a new feed additive for safe animal feeding and production.In order to detoxify ZEA, some physical, chemical, and biological methods have been conducted ,13,14,15revisiae , Bacillu ANSB01G , and Laclantarum . In thisp < 0.05) under the conditions that Candida utilis, Bacillus subtilis SP1, and Bacillus subtilis SP2 were mixed together at a ratio of A1B2C2 . The analysis showed that the optimal addition ratio of C. utilis, B. subtilis SP1, and B. subtilis SP2 was A1B1C3 . However, further ZEA degradation experiments indicated that A1B2C2 was better than A1B1C3. p < 0.01). Among the three strains of microbes, C. utilis had a significant effect on the model for ZEA degradation (p < 0.01), followed by B. subtilis SP1 and B. subtilis SP2 (p > 0.05).In order to obtain the optimal ratio of probiotics for ZEA degradation, an orthogonal design was used in this experiment. A. oryzae on ZEA degradation, the effectiveness of extracts from A. oryzae was first determined. p < 0.05); thereafter, there was no significant difference among the different groups (p > 0.05), even though ZEA degradation rate reached 98.62% after 48 h enzymatic reaction. A. oryzae was 2:1 (p < 0.05). According to this ratio, mycotoxin-biodegradation preparation (MBP) was made for the further pig feeding experiment. ZEA degradation rate of individual probiotics was lower than both combinations of probiotics and cell-free extracts of A. oryzae (p < 0.05), indicating the effectiveness of combination; however, there was no significant difference between single cell-free extracts and both combinations for ZEA degradation (p > 0.05).For measuring the effect of combined probiotics with cell-free extracts of p > 0.05). However, it showed that the above parameters could be improved by MBP addition in groups D and E, compared to group B.In order to determine the effect of MBP on alleviating ZEA for pig production performance, feeding experiments were conducted. The DGGE profile can reflect the structure of the gut bacterial community, and the number of bands indicates the richness of phylogenetic types. Gilt vulvar area can reflect the effect of ZEA on female pig reproduction status. The effect of MBP on alleviating gilt vulvar area caused by ZEA in 2). It can be concluded that ZEA or MBP could not cause significant effects on the normal physiological and metabolic status of pigs in this study.In addition, ZEA or MBP had no significant effect on serum biochemical parameters such as urea nitrogen (UN), total cholesterol (TC), glucose (GLU), triglyceride, high-density lipoprotein (HDL), low-density lipoprotein (LDL), total protein (TP), albumin (ALB), globulin (GLO), albumin and globulin ratio (A/G), alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), immunoglobulin G (IgG), immunoglobulin M (IgM), glutathione peroxidase (GSH-Px), and estradiol (Ep > 0.05), which showed that 300.00 μg/kg ZEA in pig diets was not enough to cause significant changes in relative organ weight and ERα mRNA abundance in ovaries and the uterus, even though MBP addition could alleviate ZEA hazards to some extent.ZEA may influence the relative organ weight and ERα mRNA abundance for female pigs. However, p < 0.05). ZEA concentrations in the large intestine in groups A and D were 68.57% (p < 0.05) and 12.79% (p > 0.05) lower than that in group B, respectively, indicating the effectiveness of MBP for ZEA degradation.In order to realize the status of ZEA metabolism and deposit for pigs, the ZEA distribution was measured. As one of the most ubiquitous mycotoxins, ZEA has caused serious harm to animals and humans and has led to a great waste of food resources every year . There aAcinetobacter sp. SM04 was cloned in Escherichia coli BL21 to excrete one recombinant protein for ZEA detoxification [Saccharomyces cerevisiae and B. subtilis have been found to be able to degrade ZEA around 90% [Broomyces pink and B. subtilis were reported to open the ZEA lactone ring to form nontoxic compounds by hydrolyzing lactone bonds [B. subtilis and one strain of C. utilis with good ZEA degradation abilities have been selected and combined with ZEA degradation enzymes from A. oryzae in this study. It was found that the peroxiredoxin gene from fication . Saccharound 90% ,26. Broone bonds ,28. In oA. oryzae is one kind of microbe that produces complex enzymes, which will help to increase nutrient availability and degrade mycotoxins. It was found that A. oryzae could convert ZEA into other metabolites and reduce the toxicity of toxins [A. oryzae was inoculated with corn culture medium for 21 d [A. oryzae could degrade ZEA by 98.62% after 48 h enzymatic reaction, which was better than the previous report. When cell-free extracts of A. oryzae were combined with the probiotics, the ZEA degradation rate was higher than the individual, indicating that there was a good cooperation between them. This result corresponds with the previous report for aflatoxin removal [A. oryzae extracts will have great applications in the fields of animal production and food and feed processing.f toxins . Anotherfor 21 d . In this removal . GeneralZEA is widely distributed in all kinds of grain crops and feedstuffs. The prevention and removal of ZEA pollution of grain has become a hotspot for researchers. It was found that the growth performance of weaned piglets fed with 1000 μg/Kg ZEA diet for 24 d and the young gilts fed with 1.5–2.0 mg/kg ZEA diet for 28 d had no significant changes ,33. In tSaccharomyces cerevisiae subsp. boulardii strain had the potential as feed additives to modulate bacterial populations associated with gut health for piglets [This study showed that MBP addition was able to increase gut microbial similarity coefficients to help maintain gut microbial balance for pig health, in agreement with the former research, in which it was reported that  piglets . After the diets contaminated with ZEA are fed to animals, ZEA will have three metabolic pathways: (1) ZEA is absorbed in the gut and remains in the animal’s body; (2) it is degraded by the gut microbes and enzymes; and (3) some ZEA will be discharged with the feces. It was found that the residual amount of ZEA in gilt livers increased significantly when dietary ZEA contents were 500 or 2000 μg/Kg . HoweverSerum ALT, AST, and ALP are important indicators to measure the degree of liver lesions. Serum IgG and IgM are the main factors that participate in the humoral immune response. Their normal levels in this study indicated that liver cells and immune systems have not been damaged by ZEA at 300 μg/Kg dosage. The previous report showed that long-term exposure to a low dose of ZEA had no significant negative effect on serum ALT, AST, ALP, and E2 levels in pigs , which iBacillus addition [Bacillus subtilis for degrading ZEA and keeping the microbiota stable in the pig gut [The chemical structure of ZEA is the same as estrogen; therefore, ZEA can competitively bind estrogen receptors to cause reproduction disorders, in which the red and swelling vulva of female pig is the common apparent symptom. This research showed that 300 μg/Kg ZEA could cause a red and swelling vulva; however, MBP addition was able to alleviate the symptoms, in agreement with the previous research with addition . It was  pig gut .It was found that the relative expression of estrogen receptor gene ERα mRNA in the ZEA group was significantly higher than that in control group . AnotherB. subtilis SP1, B. subtilis SP2, C. utilis) and cell-free extracts from A. oryzae could degrade ZEA effectively in vitro. MBP addition could alleviate ZEA negative effects in gilts by decreasing vulvar swelling, improving ZEA degradation in the jejunum, and keeping normal growth performance and gut microbiota stable.The combination of beneficial microbes . ZEA was purchased from Sigma-Aldrich  and diluted in methanol as stock solution (100 μg/mL). PBS buffer was prepared according to the previous protocol [B. subtilis, C. utilis, and A. oryzae incubations were prepared according to the published protocols [protocol . The comrotocols ,44. Then8 CFU/mL, respectively. The orthogonal design (5 mL reaction system) with three factors  and three levels  were used to investigate the effect of beneficial microbes on degrading ZEA. Each group contained 1 μg/mL ZEA. The contents of ZEA in the samples were determined by enzyme-linked immunosorbent assay (ELISA) according to Huang’s report [The visible counts of three kinds of microbes were adjusted to 1.0 × 10s report , which wA. oryzae was inoculated in solid medium at 30 °C for 3 d. After incubation, 15 g solid incubation was mixed with 300 mL physiological saline and put in a rotary shaker at 180 rpm for 2 h. The mixture was filtered with eight-layer gauze, centrifuged at 10,000 g for 10 min, passed through Whatman No.4 filter paper (20 to 25 µm pore diameters), and filtered with 0.22 μm Minisart High-flow filter . Finally, it was stored at 4 °C for further use.A. oryzae was determined with the previous protocol [The final volumes of 60 mL filtrates with an initial ZEA concentration of 1 μg/mL in 250 mL conical flasks were incubated at 37 °C in a rotary shaker at 180 rpm, and the samples were collected after 0, 6, 12, 18, 24, 30, 36, 42, and 48 h incubation, respectively. The ZEA degradation rates were measured at different times. The ZEA degradation activity (31.0 U/L) from cell-free extracts of A. oryzae were mixed at the volume ratios of 1:1, 1:2, 1:3, 2:1, 2:3, 3:1, 3:2, 1:0, and 0:1 as treatment groups. The final volume of the reaction system was adjusted to 3 mL with YPD medium. All the groups received 30 μL ZEA (100 μg/mL), were incubated at 37 °C in a rotary shaker at 180 rpm for 48 h, and were finally put in boiling water for 30 min to terminate the reaction. The probiotics for degrading ZEA were added in YPD medium at the above ratio. The probiotics and cell-free extracts from Group A: Basal diet with 86.19 μg/kg ZEAGroup B: Basal diet containing 300.00 μg/kg ZEAGroup C: Basal diet containing 300.00 μg/kg ZEA and 0.05% MBPGroup D: Basal diet containing 300.00 μg/kg ZEA and 0.10% MBPGroup E: Basal diet containing 300.00 μg/kg ZEA and 0.15% MBPA total of 120 young pigs (Duroc × Landrace × Yorkshire) at the ages of 78–84 d were randomly divided into 5 groups, with 3 replicates in each group and 8 pigs  in each replicate. All animals used in this experiment were managed according to the guidelines of Animal Care and Use Ethics Committee in Henan Agricultural University (SKLAB-B-2010-003-01). The pigs were provided with a corn/soybean basal diet formulated to meet pig nutrient requirements according to the NRC (2012) . The die4), and ammonium molybdate ((NH4)6Mo7O24) protocols, respectively [Fecal samples were taken without contamination from each of 5 pigs in each group for 3 d at the end of the experiment. The individual fecal sample was mixed, selected, and stored at −20 and 4 °C, respectively. The fecal samples stored at −20 °C were dried to determine nutrient digestibility. CP, CF, Ca, and P in diets and feces were measured with Kjeldahl, ether extract, potassium permanganate .Blood samples were taken from the anterior vena cava of three pigs in each group. After the blood was tilted at room temperature for 3 h, the serum was collected by Transferpettor and stored in a centrifuge tube at −20 °C for further analysis. The serum biochemical parameters such as UN, TC, GLU, triglycerides, HDL, LDL, TP, ALB, GLO, A/G, ALT, AST, ALP, IgG, and IgM were measured with a 7600-020 Automatic Analyzer  in the Biochemical Laboratory of Zhengzhou University, Zhengzhou, China. The concentrations of GSH-Px and EAfter the feeding experiment, 3 gilts from 3 representative groups  were selected and slaughtered, respectively. The gut contents were taken and frozen for further gut microbiota analysis, and the organs were taken and weighed. The formula for calculating the organ index was as follows: organ index = organ weight (g)/living weight (Kg). Some parts of ovaries and the uterus were stored in liquid nitrogen for mRNA abundance analyses.®IIqRT SuperMixII , and then kept at 25 °C for 10 min, 50 °C for 30 min, and 85 °C for 5 min. The cDNA samples were stored at −20 °C for further use. The qPCR reaction consisted of 10.0 μL AceQ® qPCR SYBR® Green Master Mix, 0.4 μL ROX, 0.4 μL Primer F (10 μM), 0.4 μL Primer R (10 μM), 2.0 μL cDNA, and 6.8 μL RNase-free water . The primers for ERα and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) genes were as follows: Forward 5′-GACAGGAACCAGGGCAAGT-3′, Reverse 5′-ATGATGGATT TGAGGCACAC-3′ for ERα; Forward 5′-ATGGTGAAGGTCGGAGTGAA-3′, Reverse 5′-CGTGGGTGGAATCATACTGG-3′ for GAPDH. The thermal program of qPCR consisted of 1 cycle at 95 °C for 10 min, 40 cycles of 95 °C for 15 s, 57 °C for 30 s, and then stored at 37 °C for 30 s. Gene-specific amplification was determined by a melting curve analysis and agarose gel electrophoresis. The cycle threshold value was analyzed (iQ5 detection System) and transformed to a relative quantity using the 2−ΔΔCT method with the highest quantity scaled to 1 [GAPDH gene was used as the reference gene for stability of expression to standardize the relative expression of the gene investigated.In order to measure the expression levels of ERα in ovaries and the uterus, the total RNA was extracted by using RNAiso Plus kits . The result was checked with 1% agarose gel electrophoresis. The reaction system for cDNA consisted of 2 μL 4 × gDNA wiper Mix, 4 μL RNA template, and 2 μL RNase-free water. It was kept at 42 °C for 2 min, mixed with 2 μL 5×HiScriptled to 1 . GAPDH gg at 4 °C for 5 min to collect the supernatant according to the previous protocol [g for 5 min to collect the pellet. The bacterial DNA was extracted with MiniBEST Bacterial Genomic DNA Extraction Kit , dissolved in 100 μL TE, and stored at −20 °C as the template for PCR amplification.About 1.0 g of gut sample from the large intestine was defrosted, put into a 10 mL centrifuge tube, washed with 5 mL PBS, and centrifuged at 500 protocol . The wasThe primers of V3 regions of bacterial 16S rRNA genes  were F34The PCR products were separated in 8% polyacrylamide gel containing a 35% to 60% gradient of urea and formamide increasing in the direction of electrophoresis. Electrophoresis was initiated by prerunning at a voltage of 200 V for 10 min and then at a constant voltage of 90 V for 14 h at 60 °C. After electrophoresis, the gel was stained with 0.5 μg/mL ethidium bromide for 30 min and then washed with deionized water for 10 min.DGGE gels were analyzed using the software of Quantity One 4.6.6 . Microbial similarity coefficients (SC) between DGGE profiles were determined as follows: SC = 2 × J/(Nx + Ny), where Nx is the number of DGGE bands in lane x, Ny represents the number of DGGE bands in lane y, and J is the number of common DGGE bands .g for 5 min, then 1 mL supernatant was mixed with 1 mL deionized water for further determination. The ZEA contents in all samples were measured by RIDASCREEN® FAST ZEA SC test kit .Longissimus dorsi, liver, and uterus tissues were ground into powder with liquid nitrogen. A total of 1 mL serum or 5 g samples were added to 25 mL 70% methanol, shaken for 3 min, centrifuged at 10,000 p < 0.05.The experimental data were analyzed as a single factor design by analysis of variance (ANOVA) using IBM SPSS-Statistics Program 20.0 , and they are expressed as means and standard errors (SEs). The means were evaluated with Tukey’s multiple range test, and differences were considered statistically significance at


Ludwigia octovalvis (Jacq.) Raven. The arsenic biosorption capability of the was also analyzed. Among the 10 isolated rhizobacteria, five were Gram-positive , and five were Gram-negative . R. radiobacter showed the highest MIC of >1,500 mg/L of arsenic. All the rhizobacteria were capable of absorbing arsenic, and S. paucimobilis showed the highest arsenic biosorption capability (146.4 ± 23.4 mg/g dry cell weight). Kinetic rate analysis showed that B. cereus followed the pore diffusion model (R2 = 0.86), E. asburiae followed the pseudo-first-order kinetic model (R2 = 0.99), and R. rhizogenes followed the pseudo-second-order kinetic model (R2 = 0.93). The identified rhizobacteria differ in their mechanism of arsenic biosorption, arsenic biosorption capability, and kinetic models in arsenic biosorption.Certain rhizobacteria can be applied to remove arsenic in the environment through bioremediation or phytoremediation. This study determines the minimum inhibitory concentration (MIC) of arsenic on identified rhizobacteria that were isolated from the roots of  Currently, most research on phytoremediation has emphasized on the physiological mechanisms of plant transport and tolerance, as well as the plant's storage of metal. A few information is available on processes in the hyperaccumulator plant phytoextraction of metals . RhizobaMany bacterial strains contain the genetic determinants of resistance to heavy metals such as arsenic, bismuth, cadmium, chromium, lead, mercury, nickel, silver, and others . The bioBacillus, Pseudomonas, and Azotobacter). PGPR such as Agrobacterium (Rhizobium), Alcaligenes , Arthrobacter, Azospirillum, Azotobacter, Bacillus, Burkholderia, Serratia, and Pseudomonas are interesting organisms for the metal extraction by plants, because they increase the rate of both metal and biomass accumulation by plants [Rhizobacteria that are capable of aggressively colonising plant roots and promoting plant growth are generally known as plant growth-promoting rhizobacteria (PGPR) . PGPR cay plants . Contamiy plants , 12. They plants , 10. They plants .Ludwigia octovalvis and increased the plant biomass. According to Nie et al. [Enterobacter cloacae have grown to a significantly higher extent than noninoculated canola plants due to the presence of arsenic. Glick et al. [Helianthus annuus after inoculation with Pseudomonas fluorescens.The interactions of rhizobacteria and plants in remediating arsenic have been studied. According to Titah et al. ; the appe et al. , canola k et al.  reportedL. octovalvis is a plant species that can survive at a crude oil-contaminated site [L. octovalvis grown in the greenhouse and contaminated land in Malacca, Malaysia. It also aimed at determining their arsenic biosorption capability.ted site  and coulted site . This stThe detailed steps of rhizobacterial isolation was described by Titah et al. .Rhizobacterial identification was conducted using two biochemical methods: Biolog GEN III microbial identification system  and Vitek2 Compact System . The detailed steps of rhizobacteria identification was described by Titah et al. .2O4·7H2O)) . Two different controls were used for this method: a PBS solution with bacteria but without arsenate (negative control) and another PBS solution with arsenate but without bacteria (positive control). Based on the study of Harley and Prescott [2HPO4·7H2O , and 2 g KH2PO4 . MIC determination was carried out in a 250 mL Erlenmeyer flask with 50 mL working volume. The pH of arsenate in sterile PBS solution was measured using Accument Basic AB 15 pH meter . The average pH readings were 7.3, 7.4, 7.5, 7.6, and 7.7 in the arsenate concentrations of 0, 250, 500, 750, and 1,000 mg/L, respectively. The cultures were incubated using an incubator shaker  at 37°C and 150 rpm. Bacterial growth was determined at an absorbance of 550 nm for 0, 3, 6, 19, and 24 h.The test was conducted using the modified method of Guo et al. . The MICPrescott , 10 × PBAn arsenic biosorption experiment was conducted using a modified published method –23. Selev/v) or 10 mg dry cell weight (DCW) was added with 50 mL of sterile PBS solution, which had an arsenic concentration of 100 mg/L by diluting sodium arsenate dibasic heptahydrate (AsHNa2O4·7H20) . The colonyforming unit (CFU) of the initial rhizobacteria was approximately 1.4 × 109 CFU/mL. A pH of 7.3 was measured for 100 mg/L arsenate in sterile PBS solution by using Accument Basic AB 15 pH meter .The biosorption of arsenic was then tested in a 250 mL Erlenmeyer flask. The rhizobacterial cell suspension at 20% . The DCW was determined after overnight drying at 105°C [All samples were tested in triplicates. All the cultures were incubated using an incubator shaker  at 37°C and 150 rpm. Samples were harvested at 0, 2, 6, 17, and 24 h. The OD was measured at 550 nm at each sampling by using Genesys 10 UV . Finally, these rhizobacterial suspensions were serially diluted, and 0.1 mL of this sample was spread onto TSA. The number of colonies grown was counted in CFU/mL. The dry weight of the rhizobacteria cells was determined by filtering the suspension culture through a vacuum filter by using 0.2 3, 1 mL of 30% H2O2, and 3 mL of sterile pure water were added to the cell pellet for 24 h. The cell samples were stored at −20°C [Ten mL of each culture was taken at each sampling time, and the supernatant and pellet were separated through centrifugation  at 10,000 rpm for 15 min. The residual amount of the total arsenic present in the supernatant was stored at −80°C  before ip < 0.05) was used to evaluate significant changes in the total arsenic concentration in the supernatant and the biosorption capability of the rhizobacteria. Correlation analysis was performed to determine the relationship between the concentration of arsenic in the supernatant and the capability of arsenic biosorption by rhizobacteria by using the Pearson correlation.All statistical tests were performed using SPSS Version 17.0 . Two-way analysis of variance (ANOVA) at 95% confidence level .In the batch experiments, kinetic studies were performed to determine the contact time of the adsorbent with the adsorbate and evaluate the reaction coefficients. To analyze the uptake kinetics, many models such as pseudo-first-order, pseudo-second-order, pore diffusion, and Elovich equation can be used. The pseudo-first-order equation of Lagergren is based on the solid capacity , whereasqe and qt are the adsorption capacities at equilibrium and at time t (mg/g biomass) and k1 is the rate constant of the pseudo-first-order adsorption (h). A linear form of the pseudo-first-order model was described by Lagergren. By integrating the equation and applying boundary conditions of t=0 to t=t, and qe=0 to qt=q at t, it becomesThe pseudo-first-order equation is generally expressed as follows:qe − qt) against t gives −(k1/2.303) as the slope and log(qe) as the intercept.A plot of log(k2 is the rate constant of pseudo-second-order adsorption (mg/g biomass/h). By applying the boundary conditions t=0 to t=t, and qe=0 to qt=q at t, the integrated form of the equation becomesThe pseudo-second-order model is used to describe the sorption kinetics . The modt/qt versus t should provide a linear relationship for the applicability of the second-order kinetics. The rate constant (k2) and adsorption at equilibrium (qeq) can be obtained from the intercept and slope, respectively.A plot of t1/2:Kd (mg/g/min1/2) is the diffusion rate constant and qt is the amount of adsorbate adsorbed at t. A plot of qt against t1/2 yields a slope of Kd. The Weber–Morris plot versus t1/2 should be a straight line with a slope Kd and intercept of C when adsorption mechanisms follow the intraparticle diffusion processes [In most adsorption processes, the uptake varies almost proportionally with rocesses . Accordirocesses , q sorptqt is the amount of adsorbate adsorbed per unit t and α and β are the Elovich constants, β is the initial adsorption rate of the Elovich equation (mg/g·h), and α is related to the extent of surface coverage (mg/g) and activation energy for chemisorption [qt against lnt yields (1/β) as the slope and (1/β) ln(αβ) as the intercept.The Elovich equation has been commonly used in determining the kinetics of chemisorption on gases and solids . Howeversorption . A plot L. octovalvis tested for their resistance to arsenate include Arthrobacter globiformis, Bacillus megaterium, Bacillus cereus, Bacillus pumilus, Staphylococcus lentus, Enterobacter asburiae, Sphingomonas paucimobilis, Pantoea spp., Rhizobium rhizogenes, and Rhizobium radiobacter. R. radiobacter had the highest MIC (>1500 mg/L), indicating that it was the most resistant rhizobacterium to arsenic (in the arsenate form). R. rhizogenes had an MIC of arsenate of 750 mg/L. The two Rhizobium species were isolated from the sand spiked with the highest arsenate concentration (80 mg/kg) [R. rhizogenes and Sphingomonas paucimobilis was inhibited at an arsenate level of 750 mg/L. The MIC of arsenate of A. globiformis, B. pumilus, Staphylococcus lentus, and E. Asburiae was 500 mg/L, while that of B. megaterium, B. cereus, and Pantoea spp. was 250 mg/L.Ten rhizobacteria from the roots of 0 mg/kg) . The groA. globiformis was higher than B. megaterium and B. cereus, which agree with the findings of Achour et al. [Arthrobacter sp. on a solid medium (Luria–Bertani (LB) agar) was 160 mM, whereas that of Bacillus sp. was 50 mM. Another study reported the MIC of arsenate for Arthrobacter sp. and Bacillus sp. on LB agar was above 75 mM [The arsenate resistance of r et al. . Accordir et al. , the MICve 75 mM .The MIC for arsenate of Gram-positive rhizobacteria was lower than that of Gram-negative rhizobacteria. This finding indicates that the Gram-negative rhizobacteria are more inhibited by arsenate or are less resistant to arsenate than Gram-positive rhizobacteria. This condition may be caused by the differences in the cell wall structure between Gram-negative and Gram-positive rhizobacteria. The cell walls of Gram-negative rhizobacteria are more complex than those of Gram-positive rhizobacteria. The cell walls of Gram-negative rhizobacteria had outer layers of membrane (OM), which selectively protects rhizobacteria from harmful substances such as antibiotics, heavy metals, and other toxic chemicals . OM contA. globiformis, B. megaterium, and B. cereus for 17 h, and decreased in the supernatant of the three rhizobacteria at the end of the exposure (24 h). The increase in total arsenic concentrations in the supernatant might be due to the conversion of arsenate to arsenite by the rhizobacteria, which is later pumped out of the cell [the cell . Botes ethe cell  reportedB. pumilus showed a different trend. Its total arsenic concentration in the supernatant increased up to 17 h and then decreased until the end of the exposure. Staphylococcus lentus also showed a different trend with increasing and decreasing arsenic concentration in the supernatant from 2 h to 24 h. In E. asburiae and Pantoea spp., the total arsenic concentration in the supernatant increased up to 6 h and then decreased. The arsenic concentration in the supernatant for Sphingomonas paucimobilis had the highest decrease at 2 h, whereas those for R. rhizogenes and R. radiobacter increased until the end of the exposure (24 hour). The arsenic removal after 24 h of the rhizobacteria can be arranged as follows: Sphingomonas paucimobilis > B. pumilus > B megaterium > B. cereus > A. globiformis > Staphylococcus lentus > R. radiobacter > E. asburiae > Pantoea spp. > R. rhizogenes.trans-acting repressor (ArsR). The ArsR protein contains a very specific binding site towards arsenite and can discriminate effectively against phosphate, sulphate, cobalt, and cadmium. Although ArsR is specific for arsenite, the removal of arsenate may occur through the initial conversion of arsenate into arsenite by arsenate reductase and subsequent sequestration by ArsR [Arsenate enters the bacterial cell wall through a fast, unspecific, and constitutive uptake system for phosphate . Arsenat by ArsR .p < 0.05). The total arsenic concentration in the supernatant for Sphingomonas paucimobilis was significantly different (p < 0.05) compared with those of the other nine rhizobacteria at 0 h. However, at 24 h, the total arsenic concentration in the supernatant for Sphingomonas paucimobilis was significantly different (p < 0.05) than those of the seven other rhizobacteria but was not different (p > 0.05) from R. rhizogenes and R. radiobacter.The results of ANOVA show that the total arsenic concentration in the supernatant was significantly different depending on the rhizobacteria species and the exposure time (Sphingomonas paucimobilis had the highest arsenic biosorption (146.4 ± 23.4 mg/g DCW) at 2 h. The maximum arsenic biosorption of B. cereus, B. megaterium, and B. pumilus occurred at 24 h with 16.8 ± 4.2, 15.4 ± 3.1, and 9.4 ± 0.6 mg/g DCW, respectively. According to Shakya et al. [B. cereus decreased from 24 to 96 h of exposure. Another study reported that the maximum arsenic accumulation of Bacillus spp. strain DJ-1, which was observed during the stationary phase of growth, was 9.8 ± 0.5 mg/g DCW [A. globiformis at 24 h was 32.2 ± 5.0 mg/g DCW. The arsenic biosorption of Staphylococcus lentus increased up to 6 h (19.2 ± 2.8 mg/g DCW) and then decreased up to 24 h (2.8 ± 0.6 mg/g DCW). The arsenic biosorption of Pantoea spp. decreased up to 6 h (2.0 ± 0.2 mg/g DCW), increased, and then decreased to 24 h (4.8 ± 0.3 mg/g cell dry weight). The arsenic biosorption of E. asburiae increased up to 17 h (13.5 ± 1.9 mg/g DCW) and then decreased at 24 h (8.7 ± 3.7 mg/g DCW). The arsenic biosorption of R. rhizogenes and R. radiobacter declined with arsenic levels of 11.2 ± 0.1 to 3.9 ± 0.1 and 25.9 ± 0.4 to 4.3 ± 0.9 mg/g DCW, respectively. The average arsenic biosorption capability after 24 h of the rhizobacteria can be arranged as follows: Sphingomonas paucimobilis > A. globiformis > R. radiobacter > B. pumilus > Staphylococcus lentus > B. cereus > Pantoea spp. > R. rhizogenes > E. asburiae > B. megaterium.a et al. , the accmg/g DCW . The arsp < 0.05). However, the exposure time did not significantly differ (p > 0.05). The LSD analysis on the capability of arsenic biosorption indicates that the arsenic biosorption capacity of Sphingomonas paucimobilis and A. globiformis was significantly different (p < 0.05) compared with the other eight rhizobacteria.ANOVA shows that the arsenic biosorption capabilities differed significantly among rhizobacteria species  cells. Sphingomonas paucimobilis cells with elongated ) had thickened and wrinkled both the cell wall and the cell plasma membrane. Sphingomonas paucimobilis cells grown at an arsenate concentration of 750 mg/L were smaller than those grown under the control medium . The plot for both biosorbents resulted in an R2 of 0.82 (B. cereus) and 0.91 (E. asburiae). This finding indicates that the pseudo-first-order model of Lagergren best explains the arsenic biosorption of E. asburiae and B. cereus. The qe and k1 obtained from the intercept and slope of equations , indicating that the pseudo-second-order model was favourable for the arsenic biosorption by R. rhizogenes. The obtained qe was 6.02 mg As/g biomass, while the obtained k2 from the intercept was 0.5 mg As/g biomass/h  have different MICs after exposure to arsenate. R. radiobacter was the most resistant rhizobacteria to arsenate with a MIC >1500 mg/L. All rhizobacteria were able to biosorb arsenic. Sphingomonas paucimobilis showed a higher arsenic biosorption (146.4 ± 23.4 mg/g DCW) than the other nine rhizobacteria. All the resistant rhizobacteria have the potential as PGPR to enhance the arsenic phytoremediation. Based on the kinetic rate, B. cereus, E. asburiae, and R. rhizogenes had the highest R2 value of 0.86, 0.99, and 0.93 under the pore diffusion, pseudo-first-order kinetic, and pseudo-second-order kinetic models. It can be concluded that the MIC, arsenic biosorption capacity, and kinetic models in arsenic biosorption depend on the rhizobacterial species.Ten isolated rhizobacteria from


Mauritia flexuosa (Arecaceae), known as “Buriti,” is a Brazilian palm tree with high economic potential for local communities. Herein, we investigated the phytochemistry profile and antioxidant potential of M. flexuosa fruits and determined the bioaccessibility of phenolic compounds. Peels revealed upper values for phenols, flavonoids, carotenoids, tannins, and ascorbic acid when compared to the pulps and endocarps. All samples showed capacity to scavenger free radicals  but peels presented higher scavenger action in all methods explored. Phenolic compounds identified by HPLC displayed reduced bioaccessibility after in vitro simulated gastrointestinal digestion for pulp (38.7%), peel (18.7%), and endocarp (22.3%) extracts (P < 0.05). Buriti fruits also protected rat blood cells against lysis induced by peroxyl radicals. We demonstrated the promising chemopreventive potentialities of M. flexuosa fruits and their by-products and peels with higher quantities of bioactive compounds and phenolic substances before and after in vitro bioaccessibility investigation. In Brazil, these parts are discarded or underused, mainly as feed for ruminant animals. Consequently, it is extremely important to explore nutritional characteristics of these by-products for human/livestock foods and to install biofriendly techniques and sustainable biotechnology handling of natural resources. Bioactive compounds have natural functions in plants such as sensory properties  and defense against microorganisms and predators . On the In this context, plant species produce secondary metabolites belonging to different chemical groups such as alkaloids and cyanogenic glycosides and nonnitrogenous compounds, such as tannins, flavonoids, terpenes, and anthocyanins, which present antioxidant activity –12. Mauritia flexuosa L. f., belongs to the family Arecaceae, a palm tree widely distributed in South America, especially in the Amazon region and Brazilian Cerrado, where it has demonstrated high economic potential for the biotechnology development based on the sustainability of natural resources. In the Brazilian food industry, the peel and endocarp are commonly discarded or underutilized for the preparation of candies, ice creams, juices, jams, porridges, and/or oils  , 2,2′-azH∙] [∙+] , reducin3+/Fe2+] , lipid p3+/Fe2+] , 34, and3+/Fe2+] , 36. Aqu50) for Buriti extracts were spectrophotometrically quantified  at 515 nm for DPPH∙, 734 nm for ABTS∙+, 700 nm for potassium ferricyanide, 532 nm for TBARS (thiobarbituric acid reactive substances), and 540 nm for nitrite radicals 30 min after the reaction started. Antioxidant evaluation was performed in triplicate from two independent experiments and absorbance values were converted to the inhibition percentage (I) of radicals using the equation of [∙ solution and absorbance of sample is the absorbance for reaction mixture (DPPH∙ and sample).Values of 50% effective concentration (ECation of : (%) = [ Colégio Brasileiro de Experimentação Animal) and international guidelines on the care and use of experimental animals (Directive 2010/63/EU of the European Parliament and of the Council).All procedures were approved by the Committee on Animal Research at UFC (#054/2014) and they are in accordance with Brazilian  with ketamine  and xylazine . Blood was mixed with 0.85% NaCl solution containing 10 mM CaCl2 and submitted to three centrifugations (2000 rpm/5 min). Erythrocytes were suspended in NaCl to obtain a cell suspension (10%). Hemolytic investigations were performed in 96-well plates following the method described by [Blood was collected from retroorbital plexus of anesthetized femaleribed by .μL of 0.85% NaCl. The first well was the negative control that contained only the vehicle (PBS), and in the second well 50 μL of test substance that was diluted in half was added. The extracts were tested at concentrations ranging from 0.5 to 8 g/mL. The last well received 50 μL of 0.2% Triton X-100  to obtain 100% hemolysis. Then, each well received 50 μL of a 10% suspension of mice erythrocytes in 0.85% saline containing 10 mM CaCl2. After incubation at room temperature for 2 h, cells were centrifuged, the supernatant was removed, and the liberated hemoglobin was measured spectroscopically as absorbance at 540 nm. For comparison, a solution of 0.5 mg/mL Triton X-100 was used as positive control.Each well received 50 μL of 10% erythrocyte suspension and 50 μL of AAPH  in 96-well plates. The reaction mixture was incubated for 120 minutes at 37°C. Afterwards, the reaction mixture was diluted with 240 μL of PBS and centrifuged at 2000 rpm for 5 min and the liberated hemoglobin was measured spectroscopically as absorbance at 540 nm. Results were expressed as percentage inhibition of hemolysis compared to the complete hemolysis of erythrocyte suspensions induced by AAPH. Liberated hemoglobin was measured spectroscopically as absorbance at 540 nm. The inhibition of erythrocyte hemolysis was calculated as (1 − Asample/Acontrol) × 100%. Trolox (0.5 mg/mL) was used as positive standard.The antioxidant capacity against oxidative hemolysis was performed by inhibition of oxidative hemolysis induced by peroxyl radicals generated following thermal decomposition of 2,2′-azobis(2-amidinopropane) dihydrochloride (AAPH) in method described by  with somμL for the standards substances and samples was injected for each HPLC analysis.For chromatographic analysis, methanol extracts of pulp, peel, and endocarp were used. Mobile phases were represented by solvents A–C using three pumps associated with the chromatograph . A TSK-GEL Super-ODS (Supelco) column was used. The effluent was monitored at 250 and 330 nm. Flow rate was fixed at 1.0 mL/min, and column temperature was maintained at 37°C throughout the test. Initially, the solvent was represented by 100% solvent B, but a linear gradient was used to increase solvent A from 0 to 10% within 7 min. Its composition was maintained at an isocratic flow for 3 min. Then, solvent A increased from 10 to 40% during 20 min. Such composition was maintained for additional 2 min and returned to the initial condition in 3 min. A volume of 20 50 values were calculated by nonlinear regression (95%). Statistical correlation among experimental data was performed using the Pearson coefficient (r) and results were statistically significant when P < 0.05.Data were presented as mean ± standard error of the mean (SEM) and compared by one-way analysis of variance (ANOVA) followed by Student-Newman-Keuls test using GraphPad Prism® software 5.0 . EC M. flexuosa fruit is described in βCTE/100 g), tannins , and ascorbic acid (5.9 ± 0.2 mg/100 mL) when compared to the pulp and endocarp (P < 0.05).The screening of bioactive compounds intR) with reference standards .Subsequently, we analyzed the quantity of phenolic compounds before and afterendocarp . All samIn this step, we carried out quantification of the antioxidant capacity of Buriti samples  at concentrations of 0.5, 1, 2, 4, and 8 mg/mL. This capacity is described as free radical inhibition .50 values: 1.6 ± 0.1, 0.1 ± 0.1, and 1.5 ± 0.1 mg/mL (DPPH∙); 2.3 ± 0.1, 0.1 ± 0.1, and 1.9 ± 0.1 mg/mL (ABTS∙+); 2.1 ± 0.3, 1.2 ± 0.1, and 1.9 ± 0.4 mg/mL (potassium ferricyanide); 1.6 ± 0.2, 0.7 ± 0.1, and 2.3 ± 0.2 mg/mL (TBARS); and 2.6 ± 0.1, 1.1 ± 0.1, and 6.4 ± 0.14 mg/mL (nitrite content) for pulp, peel, and endocarp, respectively. Trolox (0.5 mg/mL), the positive standard, showed free radical inhibition capacity upper to 90% for the antioxidant assessments (P < 0.05).For all parameters and samples, we determined ECessments . Then, aFirstly, we analyzed the capacity of the samples to cause hemolysis. None of the extracts induced lysis of rat erythrocytes even 8.0 mg/mL. On the other hand, Triton X-100, used as positive control, caused 100% hemolysis.50 values were 7.7 ± 0.4, 1.8 ± 0.1, and 11.4 ± 0.5 mg/mL for pulp, peel, and endocarp, respectively.Based on these promising findings , we evaluated the antioxidant capacity against oxidative hemolysis induced by AAPH (100% hemolysis). Once again, all concentrations used  were able to protect blood cells when compared to positive control exposed to peroxyl radicals generated following thermal decomposition of AAPH as follows: pulp , peel , and endocarp , respectively . Trolox r > 0.881; P < 0.05) and bioactive compounds and protection against oxidative hemolysis  (P > 0.05).Pearson's correlation, a measure of the strength of linear relationship between two variables, revealed a positive relationship between bioactive compounds  and antioxidant capacity ( < 0.05) . On the  M. flexuosa fruits.Since oxidative damage contributes significantly to pathologies, herein, we performed different biochemical methods to support the antioxidant and functional action of M. flexuosa fruits presented highest values of bioactive compounds when compared to the pulp and endocarps. Previously, studies demonstrated that pulp extracts from Amazon Buriti have mainly quinic acid, caffeic acid, chlorogenic acid, ferulic acid, p-Coumaric acid, protocatechuic acid, catechin, epicatechin, luteolin, apigenin, myricetin, kaempferol, and quercetin, some of them also found in lower concentrations [μg/100 g), especially α- and β-carotene and cis- and trans-ᵞ-carotene [Peels fromtrations . Moreovecarotene –43, whicOur results presented differences per 100 g of dry material, since Buriti samples were collected under natural conditions from Cerrado Brazilian (a type of savanna) and most studies presented outcomes with fruits from Amazon region. These findings are explained by differences in biome conditions. Amazon is hot and humid, while Cerrado presents a dryer climate. Besides, the Cerrado soil is more acid and rich in aluminum salts, which will probably generate higher oxidative stress for the plants. They react, producing antioxidant agents . in vitro antioxidant activity do not necessarily have similar actions after gastrointestinal process and absorption [ in vitro method that has recently gained much attention because it simulates the process of gastrointestinal digestion, enabling studying changes that occur in the diet components during gastric and intestinal digestion. Moreover, in vitro techniques have the advantage to substitute animals and are time-efficient and cost-effective and require less manpower [ M. flexuosa methanol extracts showed reduction of bioaccessible polyphenols after digestion simulation ranging from 18.7 (pulp) to 38.7% (peel).Polyphenol substances with highsorption , 44. Themanpower , 44, 45. Lactobacillus and Bifidobacterium genera), leading to the production of lactic acid, short-chain fatty acids, and gas, events that can alter food components and their bioavailability [It is important to note that only solubilized nutrients from the food matrix which are not destroyed during gastrointestinal digestion are bioaccessible and potentially bioavailable , 23. Sinlability . Furtherlability . M. flexuosa fruits have been associated with multiple nutritional properties that can be favorable to the human health, their fibers and polyphenols may link to macromolecular compounds that are not dialyzable or generate mineral complexes, further decreasing solubility and bioaccessibility of phenols [ in vitro gastrointestinal digestion separates bioactive substances, this can interfere with biological activity and quantity of phenolic compounds, which may work more efficiently together rather than individually as synergists to reduce free radicals [Although phenols , 48. Furradicals . Anacardium occidentale L., another typical natural delight from Brazilian Northeast known as “caju,” “acajuíba,” and “açajaíba,” but more popular, accepted, studied, and economically exploited than M. flexuosa, also showed a considerable loss of phenolic compounds in cashew apple juice and cashew apple fiber after bioaccessibility tests, mainly due to the type of food matrix elements, and this often alters absorption of phenolic compounds [Investigators working with cashew fruits fromompounds . In vitro antioxidant activity is mainly based on chemical assays that assess the ability of a substance to reduce the concentration of free radicals in a specific reaction medium [ in vitro scavenging actions.n medium , 51. The∙+) by addition of sodium persulphate and is reactive towards most antioxidants. Since it is not affected by ionic strength, it can be used to determine both hydrophilic and hydrophobic antioxidant capacities [Firstly, we used the DPPH method, since it is a rapid, simple, accurate, and inexpensive assay for measuring the ability of different compounds to act as free radical scavengers or hydrogen donors and to evaluate the antioxidant activity of foods and beverages independent of sample polarity , 52. In pacities . The totpacities . Subsequpacities , 34. Finpacities , 36. It pacities . Mauritia flexuosa. Differences in the antioxidant action found are probably associated with distinctive concentrations of the chemical constituents in each part of the plant, mainly flavonoids and anthocyanins [ M. flexuosa in the “Cerrado” biome is exposed to a higher incidence of sunlight in a soil of dry climate [Buriti samples presented antioxidant capacity, and peel extracts were more active scavengers. References  also democyanins . So, the climate . It is s climate , 55. M. flexuosa fruits (11.7 mg/mL) would correspond to 26% of the RDI, while consumption of pulp would reach 19.1%. Anyway, it is important to note that vitamin C is converted to oxalate when it is present in higher concentrations [Typically, phenols and carotenoids are found in higher concentrations in peels due to their pigmentation, regulation of enzymatic activity, and protection against sunlight and pathogenic microorganisms , 56. So,trations . M. flexuosa fruit, protection by antioxidant compounds is required and could be a reason for the higher concentration of bioactive compounds found in the peel than in pulp and endocarp. Using Pearson's correlation, we found a good correlation index among bioactive compounds and antioxidant capacity for pulp, peel, and endocarp from Mauritia flexuosa, which supports the suggestion that protection against oxidative hemolysis is directly associated with levels of bioactive substances.ForSince vegetal extracts are rich in different classes of compounds that can attack or interact with cellular membranes, hemolysis assay is frequently used to test materials, compounds, or mixture of compounds at defined pHs that mimic extracellular environments. So, the evaluation of membrane stability during exposure to phytotherapeutic products must be routinely considered in their evaluation, since the consumption of these products is increasing globally and may constitute a serious public health problem. So, membrane stability represents the capacity of this biological complex to maintain its structure under chaotropic conditions such as hypotonicity, pH extremes, heat, and the presence of solutes  and oxidative stress , 58–60.  M. flexuosa may be associated with an osmotic stabilization of erythrocytes. It is possible that the exacerbation of Van der Waals contacts inside the lipid bilayer could be a source of membrane stabilization, though such membrane protection is normally related to the prevention of lipoperoxidation triggered by secondary metabolites such as flavonoids and phenols that can be incorporated into erythrocyte membranes [The antihemolytic action described for fruit extracts fromembranes , 58, 61.embranes . Such prembranes , 62, antembranes , lowerinembranes , 64, andembranes , 41 acti M. flexuosa fruits and their by-products showed promising chemopreventive potentialities, and peels demonstrated higher quantities of bioactive compounds and phenolic substances before and after in vitro bioaccessibility investigation. Since the processing of M. flexuosa fruits generates a large quantity of agricultural residues such as peels, endocarps, and seeds, most of them are commonly discarded or are used as feed for ruminant animals only, especially after production of sweets and oil extraction. Consequently, it is extremely important to explore the nutritional characteristics of these by-products for human/livestock foods and to install biofriendly techniques and sustainable biotechnology handling of natural resources. For Brazilian local communities, it is really important to reuse such residues, especially for people from poor regions, as a way to give better opportunities and improve quality of life.In summary, the antioxidant analysis of


Here, we investigated whether explicit feedback on the result of the action (success or failure) modified sense of agency (SoA) in a continuous action task. Participants carried a white dot with a delay to a target square while avoiding obstacle squares. The color of the target changed unpredictably between white and blue. A trial was considered as successful or failed if the dot reached the target while it was white or blue. Thus, actions during the task resulted in almost identical experiences of successful and failed trials. After each trial, the participants reported to what extent they felt that they had been in control of the dot. The results showed that SoA was higher with shorter delay  and in the successful trials. These findings indicate that the sense of online control and the evaluation of continuous action based on feedback independently influence SoA. Particularly, the evaluation retrospectively modulated SoA. Sense of agency (SoA) is a subjective feeling that one is controlling one’s own actions and one’s action causes changes in external circumstances –2. NumerThe comparator model  suggests that SoA basically arises from internal cueing and is determined by a match between a sensory prediction of an action’s consequence and the actual consequence –12. If tIn the present study, we were interested in how SoA emerges during continuous action –8. In daIndeed, Wen and colleagues did show that SoA during continuous action was influenced by not only the action–feedback association  but also by goal-directed inference , which represents high-level cognition arising from the fact that the participant was able to achieve a given task . Their rIn the present study, we aimed at isolating the effects of feedback of results on SoA. To do so, we adopted the dot control task ,18, but Twenty-two volunteers  participated in the experiment. All participants had normal motor function and were naïve to the purpose of this study. This experiment was approved by the institutional review board (IRB) of Waseda University (2015–033), and conducted in accordance with the ethical standards in the 1964 Declaration of Helsinki. Written informed consent was obtained from all participants in advance.We prepared three types of stimuli; dot, target, and obstacle . At the Two independent variables were prepared to modulate task difficulty: delay and number of obstacles. Two types of delay between key press and the reaction of the dot were prepared: 250 ms and 750 ms, which was fixed within a trial. In addition, the number of obstacles was determined for each trial: one or four .The participants were instructed to move the white dot to the target as quickly as possible and reach the target when the target’s color was white . For rating of SoA, we conducted three-way analysis of variance (ANOVA) with judgment type (successful or failed), two types of delay (250 or 750 ms), and the number of obstacles (one or four) as within-subject factors. Effect sizes (ηp2) were calculated for all of the ANOVAs.We independently measured reaching time, the number of key presses, and rating of SoA. For the number of trials in each judgment type , we firstly conducted one-way analysis of variance (ANOVA) with judgment type as a within-subject factor. In post hoc tests, Shaffer’s method was used where appropriate. Cohen’s SD = 7.41) and 48.05 (SD = 5.57), respectively. The mean number of failed trials by entry into obstacles was 22.09  = 66.87, p < 0.001, ηp2 = 0.76); then, post-hoc multiple comparisons with Shaffer’s method showed that the mean number of successful and failed judgment trials were larger than that of failed trials by entry to obstacles (t(21) = 9.85, p < 0.001, d = 3.47; t(21) = 8.69, p < 0.001, d = 3.60) while the number of successful and that of failed judgment trials were not significantly different (t(21) = 0.85, p = 0.40). This indicated that the present experimental paradigm did not allow participants to precisely control the dot right before entry to the target; therefore, we can assume that the efforts before entry to the target were controlled between the successful and failed trials.The mean number of successful and failed judgment trials out of 120 trials was 49.86  = 68.37, p < 0.001, ηp2 = 0.76; F = 145.61, p < 0.001, ηp2 = 0.87). The interaction between delay and obstacle was also significant  = 33.37, p < 0.001, ηp2 = 0.61). The post-hoc tests showed that the number of failed trials in the four obstacles condition was significantly larger in the delay with 750 ms than with 250 ms  = 75.79, p < 0.001, ηp2 = 0.78) and that in the delay with 750 ms was larger in the four obstacles condition than in the one obstacle condition  = 202.29, p < 0.001, ηp2 = 0.90). These results indicate that the difficulty of the present task  was modulated by delay and the number of obstacles, and in particular, control in the delay with 750 ms and four obstacles is most difficult among the experimental condition. As the present study focused on the successful and failed judgment trials, we excluded the failed trials by entry into obstacles from the next analysis.For the mean number of failed trials by entry into obstacles , we performed a 2 (delay: 250 or 750 ms) × 2 (obstacle: one or four) repeated-measures ANOVA. We found significant main effects of delay and obstacle  = 45.71, p < 0.001, ηp2 = 0.69). This indicates that the feedback of results (success or failure) affected SoA. The main effect of delay was also significant  = 16.46, p < 0.001, ηp2 = 0.44), which is consistent with the previous studies showing that a longer delay led to lower SoA [F = 0.27, p = 0.61), indicating that the number of obstacles (one or four) did not have a concrete influence on SoA. However, the interaction between trial success and obstacle was significant  = 18.41, p < 0.001, ηp2 = 0.47); post-hoc comparisons revealed that in the successful trials, SoA was higher for four obstacles than for one  = 10.56, p < 0.01, ηp2 = 0.33), and the reverse was true for the failed trials  = 5.35, p < 0.05, ηp2 = 0.20; For the average of self-rated SoA, we conducted a 2  × 2 (delay: 250 or 750 ms) × 2 (obstacle: one or four) repeated-measures ANOVA  = 0.13, p = 0.71), indicating that the reaching time did not vary by target color. The main effects of delay and obstacle conditions were significant  = 44.20, p < 0.01, ηp2 = 0.68; F = 9.01, p < 0.01, ηp2 = 0.30), indicating that delay and the number of obstacles affected the difficulty of the task. The interaction between delay and obstacle was also significant  = 7.14, p < 0.05, ηp2 = 0.25), while the other interactions were not significant  = 1.90, p = 0.18; judgment × obstacle, F = 0.67, p = 0.42; judgment × delay × obstacle, F = 0.76, p = 0.39). Post-hoc comparisons showed that the reaching time was significantly shorter in the delay with 250 ms than in the delay with 750 ms both when the number of obstacles was one and four  = 60.25, p < 0.001, ηp2 = 0.74; F = 7.03, p < 0.05, ηp2 = 0.25). With 750 ms delay, the reaching time was significantly longer in the one obstacle condition than in the four obstacles condition  = 10.21, p < 0.001, ηp2 = 0.33) while with 250 ms, it was not significantly different  = 0.02, p = 0.88).For the average of reaching time, we conducted a 2  × 2 (delay: 250 or 750 ms) × 2 (obstacle: one or four) repeated-measures ANOVA . We did F = 0.04, p = 0.85), indicating that the number of key presses did not change regardless of whether the target reached successfully or not. The main effects of delay and obstacle were significant  = 43.97, p < 0.001, ηp2 = 0.68; F = 21.50, p < 0.001, ηp2 = 0.50), indicating that delay and number of obstacles both affected the difficulty of the task. The interaction between delay and obstacle was significant  = 8.45, p < 0.01, ηp2 = 0.29), while the others were not  = 1.94, p = 0.18; judgment × obstacle, F = 0.01, p = 0.94; judgment × delay × obstacle, F = 0.003, p = 0.96). Post-hoc comparisons showed that the number of key presses was significantly larger with the 750 ms than with the 250 ms delay, both with one and four obstacles  = 47.50, p < 0.01, ηp2 = 0.69; F = 8.34, p < 0.01, ηp2 = 0.28). In the delay of 750 ms, the number of key presses was larger in the one obstacle condition than in the four obstacles condition  = 16.89, p < 0.01, ηp2 = 0.45), while with the 250 ms delay, it was not significantly different  = 0.45, p = 0.51).We conducted the same analysis for the number of key presses as for reaching time : a 2  SoA was attenuated by longer delay between key press and response. (2) SoA was higher in the successful trials than in the failed trials. (3) The differences of SoA between the successful and failed trials were more pronounced in the condition with more obstacles. These results indicate that SoA in the continuous task was influenced not only by the online comparison between action and outcome during the task but also by the goal-directed inference generated by the feedback of the final outcome. This supports the general notion of cue integration theory .Taking the results in turn, first, SoA was attenuated with longer delay between key press and response, as observed in the previous studies ,19–20. MSecond, the most important finding in the present study was that SoA was influenced by feedback of the final outcome even though the reaching time and the number of key presses were not significantly different between the successful and failed trials. Van der Weiden and colleagues demonstrated that SoA was low when the feedback did not match the expectation pre-determined by priming or instruction  Click here for additional data file.


Dear Editors,Pediatric Radiology on MR signal intensity changes and tissue gadolinium (Gd) retention, with emphasis on pediatric patients. On page 454 the authors reported the results of a study by Bussi et al. [A recent study by Bussi et al. [68] compared the three macrocyclic agents Dotarem, ProHance and Gadovist in rats that were sacrificed 28 days following multiple administrations of one of these GBCAs. The authors found significantly lower concentrations of gadolinium in rats injected with Dotarem when compared to the other two agents, in the cerebrum, cerebellum, femur and renal tissues.” Later, on the same page, the authors stated the following: “Furthermore there are differences between macrocyclic agents that are related to their chemical stability, with a higher clearance rate of Dotarem, which is ionic and hence more stable than ProHance and Gadovist.” These statements are factually incorrect.We read with interest the article by Dr. Blumfield et al.  in the Mi et al. , making P<0.001), in the cerebellum; 0.116±0.036 vs. 0.250±0.032 and 0.263±0.045 nmol/g, respectively (P<0.001), in the cerebrum; 25±13 vs. 139±88 (P<0.01) and 204±109 nmol/g (P<0.001), respectively, in the kidneys. Significantly (P<0.001) higher gadolinium levels were noted in the femur with Gadovist (8.60±2.04 nmol/g) compared to Dotarem (5.69±1.75 nmol/g) while the mean value for ProHance (7.48±1.37 nmol/g) was only marginally significantly higher than the mean value for Dotarem (P<0.05).In the study in question, Bussi et al.  made 20 It is worth emphasizing that other authors have similarly found lower levels of gadolinium in rat brain and body tissues after administration of ProHance compared to Dotarem and Gadovist, particularly in the first days and weeks after administration, indicating a more rapid clearance of ProHance than Dotarem or Gadovist , 4. The In conclusion, Dr. Blumfield et al.  have mis


Optical microscopy clearly showed the drops of the internal phase surrounded by droplets of oil dispersed in the second aqueous phase; the droplet size was higher for CMT and lowest for CMW. In addition, all emulsions were highly stable at creaming and were effective in reducing the loss of antioxidant activity (88.82%) and total phenols (64.26%) during storage; CMT, CML and CM were the most effective. Furthermore, all emulsions showed a protective effect by modulating the release of the GTE in a simulated gastrointestinal environment, allowing a controlled release during the gastric-intestinal digestion phases and reaching its maximum release in the intestinal phase (64.57–83.31%). Thus, gelled double emulsions are an alternative for the preservation of GTE and could be a potential alternative for their application in the development of functional foods.The aim of this research was to develop and characterize five gelled double emulsions based on chia mucilage (CM) and different biopolymers  loaded with green tea extract (GTE). Gelled double emulsions consisted of W Camellia sinensis L. plant native to China and is one of the most popular and beverages consumed around the world [Nowadays, consumers are focusing their attention on the consumption of high-quality foods that provide basic nutritional properties and provide beneficial effects to health, reducing the risk of disease ,2. Greenhe world ,4. Greenhe world ,6. Due the world ,8. In rehe world ,10. Howehe world ,11. Amonhe world , spray-dhe world , freeze he world , electrohe world , liposomhe world , high shhe world , nanoemuhe world , film fohe world , simple he world  and doubhe world ,22.1/O/W2) are systems consisting of an internal aqueous phase (W1), trapped as small drops within larger oil droplets (O), which are subsequently dispersed in another aqueous phase (W2) [1/O/W2) based on extra pure paraffin oil/cetyl dimethicone copolyol/polysorbate 80) incorporated with GTE (5%). However, although such emulsions were stable enough against any phase separation, some parameters, such as pH, viscosity and conductivity, were not impressive enough to assume multiple emulsions in the long term (30 days) [1/O/W2) based on cetyl dimethicone copolyol (lipophilic emulsifier) and a blend of polyoxyethylene (20) cetyl ether and cetomacrogol 1000® (hydrophilic emulsifiers) with the presence of a thickener and hydroxypropyl methylcellulose (HPMC); these thickeners considerably improved the stability of W1/O/W2 for a period of 12 months.Double emulsions (Wase (W2) ,24,25. Dase (W2) ,27. Ther30 days) . In anot30 days)  evaluateSalvia hispanica L.) is an herbaceous plant originally from southern Mexico. Chia seed consumption is related with beneficial effects on health due to its high levels of protein, minerals, vitamins, antioxidants and dietary fiber (5–6% of mucilage) [On the other hand, chia (ucilage) ,29,30. Cucilage) . CM is aucilage) ,29. Receucilage) . In addiucilage)  found thTM , locust bean gum (L), and κ-carrageenan (C) were acquired from Gomas Naturales, S.A. de C.V. . Whey protein concentrate (W) was purchased from Ingresa México S.A. de C.V. . Polyglycerol polyricinoleate  was donated by Millikan, S.A de C.V . Free radicals; 1,1-diphenyl-2-picrylhdrazyl (DPPH+), 2,2′-Azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS+) and 6-hydroxy-2,5,7,8-tetramethylchroman-2 carboxylic acid (Trolox) were obtained from Sigma-Aldrich Química, S. de R. L. de C.V. . Ethanol, n-hexane, acetone, sodium azide and sodium chloride were purchased from Desarrollo de Especialidades Químicas S.A de C.V .GTE was obtained from Organic by the Cup S.A. de C.V. Canola oil and chia seed were purchased from a local supermarket in Monterrey, Nuevo León, México. Thixogum2 and then freeze-dried for 24 h [GTE was extracted by constant magnetic stirring  with an ethanolic solution (80%) at a constant ratio 1:100 (w/v) for 4 h. Subsequently, the solution was subjected to an ultrasonic bath (conditions), filtered under vacuum (Whatman filter paper No.1), and ethanol was evaporated in a rotary evaporator . The concentrated solution was kept frozen with COfor 24 h . Yield w• Antioxidant Activity and Total Phenol Content−1) was measured using the DPPH+ and ABTS+ methods during 35 days of storage . Trolox was used as a standard reference. A DPPH+ radical scavenging assay was determined following the method of Thaipong et al. [2 = 0.99. Antioxidant activity values were expressed as µmol Trolox equivalent (TE) mL−1.Antioxidant activity of GTE  and allowed to react with a potassium persulfate solution (2.45 mmol L−1) at a 1:1 ratio (v/v) for 16 h at 25 ± 2 °C in dark conditions, the absorbance then being recorded by a spectrophotometer at 734 nm (absorbance = 0.700 ± 0.02). Aliquots of GTE (150 μL) were mixed with ABTS+ solution (2.7 mL), the mixture was allowed to react for 6 min at 25 ± 2 °C in dark conditions and the absorbance was recorded at 734 nm. Finally, a standard calibration curve of Trolox was determined for the ABTS+ radical at concentrations ranging from 0 to 300 μmol. The curve equation was y = 0.4387x + 3.7833, R2 = 0.99. Antioxidant activity values were expressed as µmol TE mL−1. Additionally, antioxidant activity for both the DPPH+ and ABTS+ methods was calculated as a percentage of inhibition according to the following equation:Moreover, an ABTS+ radical scavenging assay was measured according to Jin et al.  with som3CO2  was subsequently added and allowed to react for 90 min. Absorbance was measured at 734 nm. A standard calibration curve was determined for catechin at concentrations range of 20–180 μmol L−1. The curve equation was y = 0.0037x − 0.0162, R2 = 0.99. Total phenol content was expressed as µg catechin equivalents (CE) mL−1.Finally, total phenol content was determined by the Folin–Ciocalteu method as reported by Thaipong et al. , with soCM extraction was carried out according to the methods reported by Capitani et al.  and Timi1) was prepared dissolving WPC, sodium azide, NaCl and GTE  into distilled water by constant magnetic stirring (2 h), and the oil phase (O) was prepared by dispersing PGPR into canola oil at 50 °C to reduce the viscosity of these solutions. The W1 phase  was dispersed into the O phase with a high-power homogenizer  at 7500 rpm for 5 min−1 (primary emulsion). Five different solutions for the external aqueous phases (W2) were prepared; CM  and in combinations (1:1), CMC (chia mucilage/κ-carrageenan), CML (chia mucilage/locust bean gum), CMT (chia mucilage/thixogum) and CMW (chia mucilage/whey protein concentrate) by constant magnetic stirring until completely dissolved; concentrations were established based on previous experiments (data not shown). Finally, the W1O phase was dripped into the W2 phase (ф2 = 0.2), followed by mixing with a high-power homogenizer at 7500 rpm for 5 min−1 . Finally, gelled double emulsions obtained were stored at 4 °C for 35 days. The compositions of the gelled double emulsions are shown in The inner aqueous phase  were obtained using a conventional optical microscope  equipped with a camera and Image pro plus 4.0 software. The emulsions were observed with a 100× magnification objective, using immersion oil.• Droplet Size Determinations4,3 and D3,2 µm). Measurements were made at days 0, 7, 14, 21, 28 and 35 of storage, respectively.Droplet size measurements of the gelled double emulsions were made using static light scattering with Mastersizer 3000 equipment . Results were expressed as the mean droplet size −1 previously prepared in a solution of HCl 0.1 M) and distilled water to obtain a final volume of 40 mL. This solution remained under constant stirring for 2 h at 37 °C in dark conditions (0–120 min). After gastric digestion, the pH of the solution was adjusted to 7 by addition of NaHCO3 (0.045 M) and a pancreatin-bile solution  was added; the mixture was stirred at 37 °C for 2 h in dark conditions . GTE released throughout gastric  and intestinal  conditions was calculated by measuring the samples (600 μL) obtained directly from the gastrointestinal medium at different times, by the antioxidant activity method (ABTS+) as reported in a previous section  and microscopic images of the gelled double emulsions during the in vitro digestions process were obtained as reported in a previous section . Statistical analysis of the data was performed using SPSS software . Data were analyzed through a variance test (ANOVA) and a Tukey test. Differences between means were considered significant at p values ≤ 0.05.All determinations were carried out in triplicate , similar to the reported by Unno and Osakabe .−1  and for ABTS+ between 9164.26 and 1685.45 μmol TE mL−1 . Similar results have been reported by Wang and Liang [p < 0.05; 88.82% and 81.60% for DPPH+ and ABTS+, respectively). On the other hand, GTE showed an initial total phenols content of 1360.49 μg CE mL−1, with a significant loss of up to 64.26% (486.14 μg CE mL−1) for day 35 of storage. Higher values of this parameter have been reported in previous studies [Results obtained regarding antioxidant activity and total polyphenol content are shown in nd Liang  and Afifnd Liang . In both studies ,42. This studies , the losCM yields obtained in this study were of 5.31% total dry matter (data not shown), similar to that found by Campos et al. . In addiGelled double emulsions based on CM and mixtures with different biopolymers  encapsulating GTE were obtained. In p < 0.05) between the gelled double emulsions (day 0), the highest value was presented by CMT  and the lowest was for CMW with values of D3,2 = 2.42 µm and D4,3 = 10.10 µm. Intermediate sizes were presented by CM, CML and CMC . However, this behavior was not found in CMW because the WPC forms a weak gel of low viscosity . Compared to the literature, particle size values lower than CML, CMC and CMT [p < 0.05), with values of 10.90 µm and 10.44 µm , respectively, for day 35 of storage. The lower droplet size values found in CMW gelled double emulsion during storage can be attributed to the fact that CMW contains a significant amount of proteins, which are surface active, and have better emulsifying properties, resulting in a more stable emulsion [p < 0.05) in the particle size was observed from day 7 of storage, with final values of 15.00, 10.26 and 19.00 µm , respectively, in accordance with previous reports [3,2 values throughout the storage period. This droplet size reduction could be associated with a leakage of water from the internal aqueous phase to the external phase of the emulsions; similar behavior has been previously reported in double nanoemulsions loaded with green tea [The droplet size was significantly different , indicating that CM and its simultaneous use with CMC, CML, CMT and CMW were an adequate alternative to stabilize the external drops in the double emulsions due to the fact that they form a thick polymeric network of strong gelation that improves the mechanical and steric stability, providing resistance to the rupture of the drops (elastic modulus (G’) of CM = 80.792 Pa, CMW = 13.463 Pa, CML = 69.020 Pa, CMT = 98.109 Pa and CMC = 564.428 Pa, at a shear rate γ = 0.1 segot shown ,51). Finot shown , who rep−1, and between 17,343.51 and 19,098.70 μmol TE mL−1 for gelled double emulsions, respectively. Regarding total phenolic content, gelled double emulsions had values ranged from 2656.36 to 4135.97 μmol CE mL−1 (−1 and ABTS+ = 9164.30 μmol TE mL−1) and total phenols . Moreover, during storage time, in general, a significant decrease (p < 0.05) was observed in the antioxidant activity values in all treatments. However, this decrease was significantly higher (p < 0.05) in GTE, indicating that the gelled double emulsions had a protective effect against the degradation of antioxidants and phenolic compounds. By the end of storage (day 35), antioxidant activity values of gelled double emulsions ranged from 1361.83 to 1839.26 μmol TE mL−1 (DPPH+) and 15,898.77 to 17,689.77 μmol TE mL−1 (ABTS+), while the total phenols fluctuated between 2312.88 and 3805.70 μmol CE mL−1; again, the CML gelled double emulsion showed the highest values in these parameters (−1 (DPPH+), 1685.45 μmol TE mL−1 (ABTS+) and 486.14 μmol CE mL−1, respectively p < 0.05) in the release of GTE was observed in CMC, CMT, CM (36.47–39.94%), followed by CMW (48.22%) and CML (8.47%), whose values were lower compared to the rest of the treatments. In addition, between 30 and 120 min a significant stability (p < 0.05) was observed in the release profile in both CML, CMT, CM and CMW emulsions . The CMC double emulsion was the most sensitive to the process of gastric digestion, presenting a constant release between 10 and 120 min (36.47%–50.05%). As reported by Lamothe et al. [p < 0.05) in the release profile was again observed in all treatments. CMC, CM and CMT gelled double emulsions were more easily digested and presented a higher release percentage at 160 min (67.98%) and 180 min (83.31% and 78.06%), respectively. In addition, CML and CMW showed their greatest release at 210 and 240 min with values of 64.57% and 74.58%, respectively. This effect may be associated with the instability of GTE catechins at alkaline pH (>6). These findings indicate that the gelled double emulsions can act as a protective barrier by modulating the polyphenol release process in a simulated gastrointestinal environment, preserving its stability and allowing a controlled release of GTE in the small intestine [The release profiles of the gelled double emulsions loaded with GTE (day 0) during the in vitro digestion process are shown in M 36.47–3.94%, folntestine ,57. Fina• Antioxidant Activity during In Vitro Digestion Processp < 0.05; −1), followed by CMW (7315.70 µmol TE mL−1). On the other hand, CMT, CM and CMC presented similar values fluctuating between 5059.73 and 5265.95 µmol TE mL−1, while the lowest value was for CML (1466.48 µmol TE mL−1). Between 10 and 120 min of the gastric digestion phase, an increase in antioxidant activity was found for both free GTE and gelled double emulsions. At the end of this process, the antioxidant activity was higher for GTE (9315.45 µmol TE mL−1) because it is free, followed by CMW (8090.60 µmol TE mL−1), CMC (7228.21 µmol TE mL−1), CM (6353.32 µmol TE mL−1), CMT (5697.15 µmol TE mL−1) and CML , followed by CMC (8365.56 µmol TE mL−1), CML and CMW , similar to that found in the release profile  was observed in the droplet size of CM , CMC , CMW , CMT  and CML , due to the effect of basic pH, bile salts and pancreatin [On the other hand, in the simulated digestion process, only slight fluctuations in particle size were found during the gastric digestion phase in all treatments, in accordance with previous reports ,59. Thes• Optical Microscopy during In Vitro Digestion Process1) to the external phase (W2), associated with the release of the GTE [In the microscopy of the gelled double emulsions at the end of the gastric digestion phase (120 min), the drops of the internal phase surrounded by oil droplets dispersed in the second aqueous phase were observed, indicating that the emulsions maintained the typical morphology of a double emulsion during this process .. On the the GTE .−1) and a high total phenolic content (1360.49 μg CE g−1), with an activity loss of up to 88.82%, 81.60% and 64.26%, respectively, in such parameters after 35 days of storage. Moreover, five gelled double emulsions based on CM and mixtures with different biopolymers  loaded with GTE were obtained. Optical microscopy of emulsions clearly showed the drops of the internal phase surrounded by droplets of oil dispersed in the second aqueous phase, which are typical characteristics of double emulsions. The droplet size of the gelled double emulsions fluctuated between 2.42 and 3.02 µm  and 10.10 and 25.48 µm , and the lowest values were for CMW while the highest values were for CMT. In general, all gelled double emulsions were highly stable at creaming and were effective in reducing the loss of antioxidant activity (up to 25.86% for DPPH+) and total phenols (15.13%) during 35 days of storage; CMT, CML and CM were the most effective. On the other hand, overall gelled double emulsions showed a protective effect by modulating the release of the GTE in a simulated gastrointestinal environment, allowing a controlled release during the gastric-intestinal digestion phases and reaching its maximum release in the intestinal phase (64.57–83.31%). Although evaluations of the in vitro digestion process provide important information on the behavior of double gelled emulsions and GTE, it is necessary to continue with this research in order to determine the effect of the gastrointestinal environment on the gelled double emulsions and GTE during different storage times. Thus, gelled double emulsions are an alternative to preserve GTE and could be a potential alternative for their application in the development of functional foods.GTE and CM were obtained with yields of 28.2% and 5.31%, respectively. GTE presented a high antioxidant activity (DPPH+ = 1868.57 and ABTS+ = 9164.30 µm TE mL


Sleep loss is associated with sleepiness, sustained attention, and memory deficits. However, vulnerability of higher cognitive processes (i.e. decision making) to sleep debt is less understood. Therefore, a major challenge is to understand why and how higher cognitive processes are affected by sleep debt. We had established in mice correlations between individual decision-making strategies, prefrontal activity, and regional monoaminergic levels. Now, we show that acute sleep debt (ASD) disturbs decision-making processes and provokes brain regional modifications of serotonin and dopamine that could explain why ASD promotes inflexible and more risk-prone behaviors. Finally, we highlight, for the first time, that in a large group of healthy inbred mice some of them are more sensitive to ASD by showing inflexible behavior and decision-making deficits. We were also able to predict mice that would be the most vulnerable to ASD depending of their behavior before ASD exposure. Using a decision-making task under ambiguity in mice completed by biochemical and neuroanatomical approaches, we characterized markers of decision-making deficits and interindividual differences regarding cognitive deficits after acute sleep debt (ASD). We highlight for the first time that in a large group of healthy inbred mice, 21% are more sensitive to sleep debt than others, showing extreme inappropriate decision-making profiles and inflexible behaviors. We were also able to predict which mice would be the most vulnerable to ASD. We feel that these exciting novel findings open new avenues and come amidst substantial efforts within the scientific community for understanding neurobiological substrates leading to individual vulnerability to ASD that is at present a matter of major interest for our society.In everyday life, we have to make frequent choices. When situations are complex, ambiguous, or novel, higher executive functions become necessary, i.e. planning, reasoning, problem solving, decision making . These eNeurobiological hypotheses explaining cognitive deficits related to ASD are not well understood. On one hand, the brain serotonergic system is involved in decision-making  and prefIndividual vulnerability to sleep debt on sustained attention and working memory processes have been shown . These iMajor challenges are to understand neurobiological systems involved in decision-making that are impaired by ASD and the reasons for individual differences in vulnerability to ASD of such higher executive functions. Animal models are an interesting way to ask such questions . We deveWe show that ASD increased impulsivity, altered decision-making strategy, DA and 5-HT level in brain areas involved in such higher cognitive processes. We also show for the first time that ASD applied before the establishment of mice preferences during a decision-making task had a more important effect on 21% of a large group of healthy mice and we were able to predict this vulnerability to ASD for 83% of them .ad libitum. For experiments in which an ASD was applied between the fifth and the sixth days we used 23 ASD mice and 23 control mice. For experiments in which ASD was applied between the second and the third days we used 28 ASD mice and 13 control mice added to the 23 control mice of the first group. For control experiments , 52 additional mice were used.The study used 139 male C57Bl/6J mice between 3 and 6 months old at the beginning of the experiments . Mice were housed by three or four, in a temperature controlled room (21°C ± 2°C), with a 12 light/12 dark cycle (lights on at 08:00 am). Experiments were performed between 09:00 am and 06:30 pm. For the sucrose preference task mice were temporally housed individually for 3 weeks. During the MGT, mice were food deprived . Water was always provided Animals were treated according to the ethical standards defined by the “Centre National de la Recherche Scientifique” for animal health and care with strict compliance with the EEC recommendations (n°86/609). Interindividual studies need a large number of animals; however, the number of animals used was reduced to the minimum.Experiments were conducted as previously described . The tasvs. 2 pellets). Despite this apparent lower attractiveness advantageous choices are advantageous in the long term because food pellets had higher probability of being found than quinine pellets. Conversely disadvantageous choices are less advantageous in the long term because animals had a higher probability of finding quinine pellets than food pellets. Therefore, mice had to favor the small immediate reward (advantageous choices) to obtain the highest amount of pellets as possible at the end of the day , the food pellet consumption (pellets earned), the number of quinine pellets obtained (but not eaten) and the latency to choose the arm during trials. We also calculated a rigidity score by measuring how many times the mouse chose the same arm. For example, a rigidity score of 25% means that the mouse chose arm by chance and a rigidity score of 100% that the mouse chose always the same arm. Therefore, a rigidity score of 50% reflected that the mouse had chosen one arm twice as much as the others, and a rigidity score of 75% that animal had chosen one arm three times more often than the others .p < 0.001) and paradoxical sleep   during sleep debt. This method was also followed by both slow wave and paradoxical sleep rebound   × 100.The sucrose preference task measured animal’s sensitivity to reward after ASD . Animalsn = 8) or not . Visit of an open arm was scored as soon as the mouse placed its two forepaws in the arm.The Elevated Plus Maze consists of two open arms (30 × 5 cm) and two wall-enclosed arms (30 × 5 × 25 cm) connected by a central platform (5 × 5 cm) . Light iExperiments were conducted as previously described , 31.Brains were removed at the end of the last day of the MGT. Animals were slightly anesthetized with Isoflurane  before cervical dislocation. Brains were rapidly removed and stored at −80°C.Brains were placed at −20°C the day before slicing. One hour before slicing, brains were brought to the cryostat and maintained at −13°C. Coronal sections (140 μm) were taken and punches (diameter: 0.75 mm) of each brain region were precisely localized using the mouse atlas .We punched six regions of interest from both hemispheres: orbitofrontal cortex , Pre and infra limbic cortex (PrL and IL), insular cortex (CIns) , the amygdala , the hippocampus (H), and caudate putamen (CPu).Amount of DA, 5-HT, 5-hydroxyindoleacetic acid (5-HIAA), and noradrenaline (NA) were quantified by using high-performance liquid chromatography (HPLC). DA turnover  was measured only in the CPu because of the high level of DA in that region.Prior to analysis, brain tissues were crushed in 350 μL of 0.2 M perchloric acid and centrifuged at 22000 g for 20 minutes at 4°C. The supernatants were collected and filtered through a 10-kDa membrane  by centrifugation at 7000 g. Then, a 20-μL aliquot of each sample was analyzed for 5-HT by fluorometric detection , 40. Thek-mean clustering analysis with Statistica software (version 12) [To distribute animals among groups according to their MGT preference we calculated for each animal the mean of the percentage of advantageous choices for the 30 last trials, i.e. when preference was stable and used a sion 12) . Each ansion 12) .F test), statistical analyses were performed using t-test. When data did not show normal distribution or pass equal variance tests, statistical analyses were performed using ranked signs Wilcoxon task, Kruskal–Wallis, or Mann–Whitney U-tests. Bonferroni correction was applied for multiple comparisons. Results were reported as means ± SEM. P values ≤ 0.05 were considered statistically significant except when Bonferroni correction was necessary.Statistical analyses were performed using Statview software. For the data that showed normal distribution (Shapiro–Wilkinson test) and passed equal variance tests  and time on mice’s preference during the MGT.The formula was as below:Y preferences or Rigidity;ASD = {0,1}, defined as ASD = 0 if ASD was not applied for this mouse and ASD = 1 if ASD was applied for this mouse;Post = {0,1}, defined as Post = 0 before ASD and Post = 1 after ASD;Vulnerable = {0,1}, defined as Vulnerable = 0 if the mean of day 1 and day 2 preferences for a mouse was above 40% of advantageous choices and Vulnerable = 1 if the mean of day 1 and day 2 preferences for a mouse was below 40% of advantageous choices;ε as the error.H0 was defined as “there is no effect of ASD.” Therefore, if P values ≤ 0.05, H0 is rejected and we concluded that we have an effect of ASD.U = 244.000, p = 0.65; day 2 t = −0.369, p = 0.71; day 3 t = −0.034, p = 0.97; day 4 U = 261.500, p = 0.95; day 5 t = −0.420, p = 0.65; day 6 U = 231.500, p = 0.47). Mice preferences for advantageous options increased over time only for the control group . We observed that mice preference for advantageous choices had only a tendency to increase for ASD mice after day 4 .As illustrated in p < 0.01; control mice: day 1 vs. day 2, Z = −1.430, p = 0.15; day 1 vs. day 3, Z = −1.217, p = 0.22; day 1 vs. day 4, Z = −1.656, p = 0.09; day 1 vs. day 5, Z = −3.159, p = 0.001; day 1 vs. day 6, Z = −3.215, p = 0.001; ASD mice: day 1 vs. day 2, Z = −2.175, p = 0.02; day 1 vs. day 3, Z = −2.859, p = 0.04; day 1 vs. day 4, Z = −2.859, p = 0.004; day 1 vs. day 5, Z = −3.057, p = 0.002; day 1 vs. day 6, Z = −3.619, p = 0.0003), but ASD mice exhibited a response latency shorter than those of control mice on the sixth day .Mice did not differ from each other regarding their response latency except after ASD. Indeed, as shown in In summary, ASD applied after the exploitation phase decreased mice response latency and had a tendency to affect their preferences for advantageous choices.p < 0.012; control mice: day 1 vs. day 2, U = −2.117, p = 0.04; day 1 vs. day 3, U = −2.231, p = 0.02; day 1 vs. day 4, U = −2.269, p = 0.008; day 1 vs. day 5, U = −4.333, p < 0.001; ASD mice: day 1 vs. day 2, t = −2.230, p = 0.03; day 1 vs. day 3, U = −1.538, p = 0.12; day 1 vs. day 4, U = −2.066, p = 0.04; day 1 vs. day 5, U = −2.083, p = 0.03). However, preference for advantageous choices of ASD mice (ASD applied before the exploitation phase) did not differ from those of control mice .As shown in U = 340.500, p = 0.027), they significantly shifted just after ASD to very short response latency compared to control mice . During the exploitation phase, preferences for advantageous arms emerged leading both control  and ASD mice  to choose more often the same arm. The rigidity score was increased after ASD , as ASD mice chose approximately 65 ± 3.1% of the time the same arm and control mice approximately 56 ± 2.9% of the time the same arm  nor an increase of anxiety . ASD did not alter reward sensitivity  nor locomotor activity  , despite the fact that ASD and control mice consumed the same amount of food pellets  C and D. In summary, ASD had no effect on animal’s activity, stress, sensitivity to reward, pellet consumption or anxiety but led to a loss of weight just the day after ASD.U = 1.000, p = 0.01), 5-HIAA level  and 5-HT turnover  in the OFC. Moreover, ASD induced higher 5-HT level in the CIns  but no change in 5-HIAA  or 5-HT turnover , while 5-HIAA  and 5-HT turnover  were higher. We also observed a lower 5-HT turnover in the CPu  but no change regarding 5-HT  or 5-HIAA levels . Regarding PrL/IL and Amy, ASD induced no change in 5-HT , 5-HIAA , and 5-HT turnover  and DOPAC  in the CPu, but no difference could be evidenced regarding HVA  and DA turnover . ASD induced higher DA level only in the CIns and CPu , PrL/IL , CIns , Amy , hippocampus , or CPu . By contrast, animals from the “average” group (50%) developed a significant preference for advantageous options . Animals from the group “safe” (25%) developed an even more marked preference for advantageous options , i.e. “risky” animals  and “average” mice  preferred advantageous options at the end of the task compared to beginning of the task. However, ASD “risky” mice preferred disadvantageous options at the end of the task compared with the beginning . “Safe”, “average,” and “risky” groups differed from each other for the last two days .The same observation could be done for ASD mice . Indeed,H = 1.555, p = 0.46; day 2: H = 3.117, p = 0.21; day 3: H = 3.723, p = 0.15; day 4: H = 2.171, p = 0.34; day 5: H = 0.522, p = 0.77). However, subgroup strategies led ASD risky mice to obtain less food pellets  and more quinine pellets during the three last days  compared with the ASD “safe” and “average” mice  and “risky” ASD mice choosing significantly and clearly less advantageous options than “risky” control mice . Conversely, ASD did not change “average” mouse preferences , leaving this subgroup relatively unaffected by ASD . Conversely, control “risky” mice continued to explore for the entire duration of the experiment . Compared with their control subgroups, we observed exactly the same changes of the rigidity score for ASD “safe”  and “average” mice . On the contrary, ASD “risky” mice displayed a significant increase of their rigidity score over days , thus drastically drifting apart from control “risky” mice .Rigidity score is expected to change over days because mice first explored all options and then chose to exploit preferentially some of them. Control “safe” mice chose the same arm 45% of the time at the beginning of MGT and the same arm 72% of the time at the end of the task . However, ASD applied after the exploitation phase did not have any important effect on “vulnerable” mice .We defined as “vulnerable” the mice that had a mean of preference during day 1 and day 2 lower than 40%. We observed that ASD applied before the exploitation phase had a significant more important effect on these “vulnerable” mice than on the other mice. Indeed, ASD applied at this time led to 22% of decrease of their preference for advantageous choices .We also observed that ASD had a more important effect on the rigidity of these “vulnerable” mice as it increased by 30% their rigidity score at the end of the task , Amy, and hippocampus. Moreover, 5-HT levels were higher in the CIns 2 days after ASD. The role of DA in the CIns is not clearly defined, but the 5-HT system in the CIns has been linked with disgust reactions . We coulOur previous results have shown that spontaneous individual profiles emerged in control mice regarding MGT choices: “safe”, “average,” and “risky” profiles. Indeed, the majority of control mice  preferred advantageous options without neglecting alternative—potentially riskier—choices. The “safe” ones (25%) were guided by risk avoidance and were more affected by their internal state . The “riHere we also looked at the heterogeneity of animal choices after ASD and we observed that it was larger after ASD and this observation was even more obvious if ASD was performed before the exploitation phase than after. We therefore hypothesized that ASD increased variability of preference at the end of the MGT leading to a lack of improvement of advantageous choices as a group. We then used the linear regression analysis to question the possibility to predict which mice would be the most vulnerable to ASD depending of their behavior before ASD and its moment of application. We found that ASD has a drastic effect only in mice with initially risky behavior and if ASD was applied before the exploitation phase. These results are very interesting because we were able for the first time to predict an individual cognitive vulnerability related to sleep debt in mice. Moreover, these results are in accordance with human studies showing that individual differences already existing are amplified by ASD , 27, 28.Altogether, these results suggest that ASD altered decision making processes and that this observation is mostly due to an increase of heterogeneity between mice that are more or less vulnerable to sleep debt. Moreover, ASD-mediated disruption of the balance between 5-HT and DA within prefronto-striatal networks could provoke a specific decrease of behavioral flexibility and the development of nonoptimal decision-making strategies. Besides, we showed that ASD applied before the exploitation phase has a more important effect on 21% of mice. Therefore, we evidenced for the first time a cognitive vulnerability to ASD in a healthy inbred mouse population and were able to predict this vulnerability for 83% of them .