Our estimate of total variability in liver fat content (14.8%) is nearly twice that of the reported procedural variability (8.5%). We found that liver fat content was significantly inversely related to serum glycerol but not to non-esterified fatty acids (NEFA), suggesting progressive suppression of lipolysis. Reduction of caeruloplasmin with increasing liver fat may be a consequence or a cause of hepatic steatosis.Magnetic resonance spectroscopy (MRS) is a non-invasive method for quantitative estimation of liver fat. Knowledge of its imprecision, which comprises biological variability and measurement error, is required to design therapeutic trials with measurement of change. The role of adipocyte lipolysis in ectopic fat accumulation remains unclear. We examined the relationship between liver fat content and indices of lipolysis, and determine whether lipolysis reflects insulin resistance or metabolic liver disease. Imprecision of measurement of liver fat was estimated from duplicate measurements by MRS at one month intervals. Patients provided fasting blood samples and we examined the correlation of liver fat with indices of insulin resistance, lipolysis and metabolic liver disease using Kendall Tau statistics. The coefficient of variation of liver fat content was 14.8%. Liver fat was positively related to serum insulin (T = 0.48,  Nonalcoholic fatty liver disease (NAFLD) is associated with the histological finding of hepatic steatosis or steatohepatitis and has a number of causes ,2,3,4. SMagnetic resonance spectroscopy (MRS) is a non-invasive and effective method in assessment of hepatic fat accumulation with high diagnostic accuracy and correspondence with histopathologic grade being demonstrated . Impreci2 (range 20.2–40.4) with 2 patients having a BMI <25 kg/m2. MR image of the abdomen and a spectrum from the liver from one patient are shown in −1 water . Triglycerides were greater than 1.7 mmol·L−1 in 10 out of 11 patients. Hyperinsulinaemia was present in all patients although only one had a fasting plasma glucose in the impaired glucose tolerance range >6.1 mmol·L−1 and one in the diabetes range at 7.5 mmol·L−1. Nine patients had supra-normal β cell function with (homeostasis model assessment (HOMA)-B% >100%) and all patients had impaired insulin sensitivity . The distribution of differences between duplicate liver fat measurements was sufficiently normal (Shapiro–Wilk 0.7612) to calculate imprecision from the differences, with coefficient of variation 14.8%. The median body mass index (BMI) was 30.8 kg/m−1 with range 138–491 umol·L−1, and all were in the lower half of the reference range (130–1050 umol·L−1). Glycerol (reference range 27–37 umol·L−1) had a wider range of 10–210 umol·L−1 and median 90 umol·L−1 reflecting suppression with high liver fat and high levels with low liver fat. Glucose, triglycerides, alcohol intake, ferritin, iron, % iron binding capacity, and A1AT were not related to liver fat but caeruloplasmin (p = 0.5), or between groups either taking or not taking Omacor (p = 0.2).The correlations between insulin, glycerol, and caeruloplasmin and liver fat are illustrated in oplasmin c was invOur data on repeat MRS at one month intervals showed a coefficient of variation of 14.8%, which is higher than the coefficient of variation of 8.5% observed between repeat MRS taken at 10 min intervals . The normality of the distribution of differences was assessed using the Shapiro–Wilk W test. All other data are expressed as median (range) because of their non-parametric distribution. Correlation between variables was calculated as the Kendall Tau rank statistic with a 2 tailed probability of <0.05 being regarded as significant. The Kruskal Wallace one way analysis of variance test was used to assess the differences in liver fat content between 3 groups defined by drug treatment as: “no statin or fibrate treatment”, “statin monotherapy”, and “fibrate monotherapy”, which were mutually exclusive, and between 2 groups defined as “Omacor treated” or “not Omacor treated”.The standard deviation of MRS estimates of liver fat was calculated from the differences between the two scans as √ [∑ (differencesThe study was designed to estimate the variability of sequential measures of liver fat to inform power calculation for future studies. The estimate was considered sufficiently robust after 11 patients, after review by our statistician.Variability of repeat scans performed one month apart is nearly twice that observed with immediate repetition, and should be taken into account in the design of interventional trials with liver fat content as the endpoint. Glycerol is inversely related to liver fat content suggesting down regulation of fatty acid trafficking consistent with the new paradigm for the pathogenesis of fatty liver. Caeruloplasmin is inversely related to liver fat content, which is as yet unexplained.


Meanwhile, several MYB TFs have been suggested in the regulation of pH responses. These results strongly indicate that the low pH treatment-induced anthocyanin accumulation is mediated by the variation of mRNA transcription of the anthocyanin biosynthetic genes.Anthocyanin is a critical factor involved in coloration of plant tissues, but the mechanism how medium pH values affect anthocyanin accumulation in woody plants is unknown. We analyzed anthocyanin composition and the expression of elements encoding anthocyanin and flavonols biosynthesis underlying different medium pH values by using three different leave color type cultivars. HPLC analysis demonstrated that high medium pH values treatment induced a dramatic decrease in the concentration of cyaniding in crabapple leaves. Conversely, the high medium pH values induced up-regulation of the content of flavones and flavonols, suggesting that low pH treatment-induced anthocyanin accumulation. Quantitative real time PCR experiment showed the expression level of  Anthocyanins are plant secondary metabolites that are responsible for the characteristic red, blue, and purple color of plant tissues. Anthocyanins also play an important role in plant reproduction, by attracting pollinators and seed dispersers, and also in protection from stress including photo-oxidative stress In most species, the coloration of plant tissues results from the accumulation of anthocyanins pigments in the vacuoles of (sub) epidermal cells, and anthocyanins change their color depending on the pH of the vacuole in which anthocyanins localize; their color is bluer in weakly acidic or neutral pH, and redder in acidic pH Ipomoea tricolor) petals, the vacuolar pH is relatively low when the flower bud opens, resulting in a red color, but upon further maturation, the vacuolar pH increases and the petals acquire a strong blue color +/H+ exchanger encoded by the PURPLE gene PURPLE transports sodium ions into and protons out of the vacuole, resulting in a less acidic vacuole and a bluer color.In morning glory  side of the color spectrum. PH4 encodes a MYB domain protein that is expressed in the petal epidermis, mutation of PH4 results in a bluer flower color, increased pH of petal extracts, and, in certain genetic backgrounds, the disappearance of anthocyanins and fading of the flower color ANTHOCYANIN1 (AN1), AN2, and AN11 cause, besides the loss of anthocyanin pigments, an increased pH of petal extracts Malus crabapples are one of the most important ornamental and economic germplasm resources, providing abundant plant landscape species and favorable research material to exploit the mechanism of color formation, which is due to the diverse colors of its leaves, flowers and fruits as a result of different anthocyanin materials Malus crabapples, and the color of the leaves differs in different varieties. ‘Flame’, ‘Prairifire’ and ‘Royalty’ are three typical crabapple varieties and represent major leave color characteristics of crabapple. The leaves of the ‘Flame’ are green throughout the development, the leaves of ‘Prairifire’ turns green from red during development, while the leaves of ‘Royalty’ change from red to purple during development Malus crabapple cultivars. Our findings have provided strong evidence that the low pH treatment-induced anthocyanin accumulation. Flavonoid/anthocyanin biosynthetic and regulation genes respond environmental pH values by controlling anthocyanins accumulation in Malus crabapple leaves.In this study, different medium pH treatment triggered the alteration of flavonoid contents was investigated in three In order to detect how medium pH values affect seedlings development of each cultivar, we made 4 different kinds of pH values to conduct adventitious buds regeneration experiment. Multiple coefficients were determined after 30 days cultured in different medium .To explore the relationship between environmental pH values and crabapple anthocyanins variation, we conducted the leaf color measurement and the HPLC analysis of crabapple leaves in different pH values medium. As described above, crabapple cultivars ‘Flame’, ‘Royalty’, and ‘Prairifire’ are related plants but with a rather different leaf color. As shown in The variations of leaf color during leaf development were quantified using CIRG value. The results showed that the CIRG values of ‘Royalty’ and ‘Prairifire’ were gradually decreased with the increased of pH values, and the CIRG values of ‘Flame’ maintained a relative low level compared with another two cultivars. The CIRG values also suggest the leaf color of ‘Royalty’ were shifted to yellow in pH 6.5 and 7.0 .The phenolic compounds are responsible for color. Anthocyanins are one type of flavonoids, other flavonoids include flavonols, flavones. Cyanindin is one of anthocyanins and provide various red colours in plant. Flavonols and flavones are largely responsible for the production of yellow color. HPLC analysis showed that the major anthocyanins in crabapple leaves was cyanindin, and high medium pH (7.0) reduced the total cyanindin content to less than half of that in the low medium pH (5.5) in ‘Royalty’ and ‘Paraitfire’ leaves. On the contrary, increased pH value (from 6.0 to 7.0) up-regulate the content of flavones which produce yellow colors in ‘Royalty’ leaves, and the content of flavonols in ‘Royalty’ and ‘Paraitfire’ were also enhanced by increased pH treatment.The main flavonoids components in green varieties ‘Flame’ were flavonols and there was no significantly variation with different medium pH treatments . Taken tTo examine the molecular mechanisms how high medium pH values treatment induce anthocyanins accumulation in crabapple leaves An attempt was made to assess whether the changed medium pH values induced flavonoid biosynthetic genes transcription alterations in leaves.McANS and McUFGT, are response for the last reaction in anthocyanin biosynthetic pathway, were significantly higher in ‘Royalty’ and ‘Prairifire’ in acidic medium than ‘Flame’, with the highest transcript levels at pH 5.5. The expression levels of these genes were consistent with the variation of anthocyanins content and the degree of pigmentation observed during pH values variation , McF3′H (flavonoid 3′-monooxygenase) and McFLS which control biosynthetic direction to either anthocyanin or flavonol pathway, encoding anthocyanin or flavonols biosynthesis was increased 5- to 30-fold in ‘Flame’ than in another two cultivars in alkalinity conditions , McANS and McUFGT. To sum up, the different flavonoid material in three crabapple cultivars were synthesized by different anthocyanin biosynthetic genes , and McMYB2 and McMYB3 also involved in the regulation process of cyaniding biosynthesis in ‘Royalty’ . For flavonols, there are different main regulation MYB transcription factors among three crabapple cultivars, the expression trend of McMYB5 was consistent with the accumulation of flavonols in ‘Flame’ (0.91). On the other hand, flavonols concentration were positive regulated by McMYB1 and McMYB4  and negative regulated by McMYB3 and McMYB6  in ‘Prairifire’. In addition, the McMYB2 and McMYB3 transcript levels negative correlated with flavonols concentration in ‘Royalty’ . Meanwhile, the content of flavones was also negative regulated by McMYB2 and McMYB3 in ‘Royalty’ . Levels of McMYB3 and McMYB4 positive and negative associated with flavones biosynthesis in ‘Prairifire’, respectively (0.92 and −0.91). Interestingly, the expression profile of McMYB6 showed a same spatial and temporal pattern with the accumulation of flavones in ‘Flame’ (0.82).MYB transcription factors have been shown to play an important role in the transcriptional regulation of anthocyanins in apple, so we detected the expression profile of this transcription factors by different pH treatment in three cultivars , and theIpomea nil) and PH4 in Petunia can alter the anthocyanins accumulation pH values is one of important factors which affect anthocyanins accumulation. It has been previously proposed that the suitable pH for anthocyanins copigmentation is pH 3.5 Malus crabapple is becoming an excellent model plant to uncover the pigmentation mechanism In recent years, more and more attention has been paid to the breeding of color-leafed  plants for ornamental use Malus crabapple during pH treatment. The medium pH values had no obviously effect on the cyanidin accumulation and the content of flavonols in alkalinity mediums were enhanced in ever-green cultivar ‘Flame’. Flavonols biosynthesis mainly depends on the expression of McFLSMcANS and McUFGT gene was significantly different from all the other examined biosynthetic genes. Low pH treatment led to an increase in abundance of the McANS and McUFGT transcript, the pattern of expression is correlated with the pattern of cyanidin accumulation in leaves , (2) Malus ‘Prairifire’ (young leaves are orange to red and mature leaves are green) and (3) Malus ‘Royalty’ (both young and mature leaves are red to purple). These 5-year-old crabapple trees grafted on Malus ‘Balenghaitang’ were planted in Crabapple Germplasm Resources Nursery in Beijing University of Agriculture.The plant materials used for the tissue culture included three crabapple varieties: (1) Malus ‘Flame’, Malus ‘Prairifire’ and Malus ‘Royalty’ were preserved at tissue culture center of Beijing University of Agriculture. Cultural conditions: temperature was 23±2°C, humidity was 60%–70%, light intensity was 1800–2000 Lux with 16 h light a day.Tissue culture plantlet of The adventitious buds which were approximate 1.5 cm long and collected from regeneration medium were harvested and transferred to MS medium (Murashige and Skoog) with 2.2 µM 6-benzyladenine (6-BA) and 0.5 µM a-Naphthaleneacetic acid (NAA) with various pH values , The increase of fresh weight, shoot height, regeneration frequency were determined after 30 days.Quantification of pigments was performed by high-performance liquid chromatography (HPLC). One hundred milligrams of fresh petals was homogenized with a mortar and pestle under liquid nitrogen. Then 1 ml of extraction solution containing methanol∶ water ∶ formic acid∶ trifluoroacetic acid .,and the mixture was stored overnight at 4°C in the dark. The mixture was centrifuged at 4°C at 15,000 rpm for 15 min, and The supernatants were filtered through a 0.22 µm Millipore TM filter before used. Anthocyanins in the samples were analyzed using a HPLC1100-DAD system .Detection was performedat 520 nm for anthocyanin, 350 nm for flavonoid. A NUCLEODURH C18 column   was used for separation at 25°C and eluted using a mobile phase consisting of solvent A, trifluoroacetic acid ∶ formic acid∶ water (0.1∶ 2 ∶ 97.9) and solvent B, trifluoroacetic acid ∶ formic acid∶ acetonitrile∶ water (0.1∶ 2∶ 35∶ 62.9) at a flow rate of 0.8 ml min-1. The elution program was followed the procedure described previously with some modifications The flower color variables of both crabapple and tobacco were measured immediately after picking. L*, a*, and b* values were measured randomly using a Konica Minolta CR-400 Chroma Meter . The value ‘L*’ represents brightness and darkness, ‘a*’ represents greenness and redness as the value increases from negative to positive, and ‘b*’ represents blueness and yellowness. The value ‘C*’ represents saturation and was calculated according to the formula C* = (a*2+b*2) 1/2. Hue angle (h*) was calculated according to the following equation: H = arctan (b*/a*) . CIRG (Color Index for Red Grape) was calculated according to the formula CIRG = (180−H)/(L*+C) McCHS, McDFR, McF3′H, McFLS, McANS, and McUFGT were analyzed using quantitative real-time PCR (RT-qPCR) with SYBR Green qPCR Mix  and Bio-Rad CFX96 Real-Time PCR Systems , according to the manufacturers' instructions. The primers in this paper were designed by NCBI Primer BLAST and listed in Total RNA from flower tissues was extracted using an RNA Extract Kit  according to the manufacturer's instructions. DNase I  was added to remove genomic DNA, and the samples were then subjected to cDNA synthesis using the Access RT-PCR System  according to the manufacturer's instructions. The expression levels of qPCR analysis was carried out in a total volume of 20 µl containing 9 µl of 2×SYBR Green qPCR Mix , 0.1 µM specific primers (each), and 100 ng of template cDNA. The reaction mixtures were heated to 95°C for 30 s, followed by 39 cycles at 95°C for 10 s, 59°C for 15 s, and 72°C for 30 s. A melting curve was generated for each sample at the end of each run to ensure the purity of the amplified products.P<0.05 (Microsoft Excel 2003 and Data Processing System (DPS) software 7.05).All data were analyzed using one-way ANOVA followed by Duncan's SSR test (shortest significant ranges) to compare differences among the experimental sites at


Our experience with the world is shaped not only directly through personal exposure but also indirectly through observing others and learning from their experiences. Using a conditioning paradigm, we investigated how directly and observationally learned information can affect pain perception, both consciously and non-consciously. Differences between direct and observed cues were manifest in higher pain ratings and larger skin conductance responses to directly experienced cues. However, the pain modulation effects produced by conditioning were of comparable magnitude for direct and observational learning. These results suggest that social observation can induce positive and negative pain modulation. Importantly, the fact that cues learned by observation and activated non-consciously still produced a robust conditioning effect that withstood extinction highlights the role of indirect exposure in placebo and nocebo effects. Human ability to observe and imitate conspecifics likely evolved to make pain not only a personal experience but also a socially relevant behavior that solicits help and enables learning in others124567891012131416171819202224Recent studies using direct conditioning revealed that once conditioned, the cues can produce analgesia or hyperalgesia even when presented subliminally26The present study  examinedTwenty-one healthy participants with no psychiatric or neurological disorders and not taking any psychotropic medication were enrolled. One subject did not complete all experimental sessions and was excluded from the study (before the test sessions). The final sample consisted of 20 participants  with an average age of 23 ± 2 years (Mean ± SD). The Institutional Review Board at Massachusetts General Hospital approved all study procedures. The study was conducted in accordance with the approved guidelines. All enrolled subjects provided written informed consent before beginning any study procedures.www.neurobs.com).A set of fractal images was used as visual cues. Each cue was associated with one of the five experimental conditions: a high direct cue and a low direct cue were first presented during the direct conditioning sessions and associated with a high or low level of heat pain respectively; a high observational cue and a low observational cue were presented in the observational conditioning sessions and were associated with high observed pain and low observed pain respectively. In addition, a cue not associated with any pain level, either directly experienced or observed, and that did not appear during the conditioning sessions was introduced as a control stimulus during the test phase when a directly experienced, moderately painful heat stimulus accompanied all five cues. The specific assignment of fractal images to a given condition was fully counterbalanced across participants. All stimuli were presented using the Presentation® software . The average difference between the high and low temperatures during the conditioning phase was 3.1 ± 0.9 °C.Noxious heat stimuli were delivered using a PATHWAY system . All heat stimuli were initiated from a baseline temperature of 32 °C and increased to the target temperature. Each stimulus was presented for 2.5 seconds, including approximately 200 ms to ramp up to the target temperature, maintaining the temperature for 2 seconds and 350 ms to ramp down to the baseline temperature again. Heat stimuli were applied to the right volar forearm; the position of the probe was changed for every session. The mean moderate temperature used during the test phase was 46.5 ± 1.9 In order to determine the individually calibrated pain stimuli, an ascending heat pain sequence starting at 35 °C and slowly increasing by 1 °C up to 50 °C or the subject’s maximum tolerance was used. Temperatures that elicited subjective intensity ratings of low = 5, moderate = 10, and high = 15 on a scaleThe experiment consisted of six phases: 1) conditioning , 2) post-conditioning test, 3) conditioning test (2 sessions), 4) extinction (1 session), 5) extinction test (1 session), and 6) cue recognition task, conditioning phase (1), subjects experienced both direct and observational conditioning. The succession of alternating sessions: ‘direct – observational – direct – observational’ or vice versa was counterbalanced across subjects, During the During the direct conditioning trials, subjects saw two images, each consistently paired with a high or low pain level (100% reinforcement). Subjects were informed that they would see images on the computer screen and that they would experience heat pain stimulation on their arm. Subjects were told that there would be a link between the cue and the pain intensity of the stimulus that they would feel shortly thereafter. There were 10 high and 10 low cue/pain stimulus presentations in a randomized order in each of the 2 sets of trials. After each pain stimulus, the subject rated the pain felt on a 0–100 visual analogue scale (VAS), using a computer mouse and a scale displayed on the screen. The pain ratings for low and high pain were significantly different (p < 0.001); low pain elicited an average rating (Mean ± SD) of 21.2 ± 11.9 and high pain was rated 65.8 ± 12.3 on the 0–100 VAS.During the observational conditioning sessions, subjects saw two different images that were consistently paired with a high or low pain level, as during the direct conditioning trials. However, subjects did not experience pain directly, but rather watched a video clip in which a model (a research assistant in our lab) experienced a high or low level of pain stimulation to their arm. During the first set of trials, a female model was shown experiencing the pain stimulus; during the second set of trials, a male model was observed. Each trial comprising the video clip began with a side view of the model that also showed the experimental set-up, which included the heat probe placed on the hand, the computer screen, etc. After that, the conditioning cue (high or low) was displayed on the screen; it was followed by a close-up of the face of the model exhibiting a painful grimace following the high pain cue or a neutral expression after the low pain cue. At the end of the video clip, the 0–100 VAS was displayed, which appeared to be scrolled by the model to a lower (20.5 ± 6.3) or higher (73.5 ± 6.5) position on the scale to indicate the model’s pain rating. Subjects were instructed to watch each video clip and learn the association between the cues and pain levels. Similar to the direct conditioning trials, 10 high and 10 low cue/pain pairings were presented in a randomized order in each of the 2 sets of trials.post–conditioning phase (2). Mean accuracy of cue recognition was high (97.5%); only 1 subject did not identify all of the cues correctly.Following the conditioning phase, during which subjects learned the 4 different cues and their association with a high or low pain stimulus, memory of the cue/pain pairings was tested by presenting all of the cues without heat stimuli or video of the models’ responses and asking subjects to indicate whether each cue was associated with a high or low level of pain. Each of the 4 cues was repeated twice in this test phase (3), we informed subjects that they would see the 4 cues again along with an additional 5th cue that they had not seen before. Subjects were also told that half of the time the cues would appear fully visible as before  for 200 ms, and that half of the time the cues would appear very briefly  followed by a masking image (33 ms cue + 167 ms mask) so that the subject would not be able to recognize the cue (For the  the cue . All preextinction phase (4). During this phase, the 4 previously conditioned cues were presented in a random order (5 repetitions per cue) paired with a warm, but not painful, heat stimulus that was the same (34 °C) for all subjects. Subjects were presented with the directly and observationally conditioned cues during the extinction phase.Following the conditioning test, subjects underwent an extinction test phase (5) by repeating one set of trials as had been presented in the test phase (3) described above.We tested the effects of extinction during the cue recognition test (6), during which they were presented with masked and unmasked cues that were familiar, i.e., previously seen during the experiment, and unfamiliar, i.e., not previously seen, to determine whether they recognized the subliminally presented stimuli. This test was used to confirm that recognition of the subliminal stimuli was at chance level.After the extinction test, subjects underwent the In addition to the pain ratings, we also measured skin conductance levels using PowerLab 4SP GSR Amp with bipolar finger electrodes (MLT116F) placed on the distal phalanx of the index and middle fingers of subjects’ non-dominant (left) hand and LabChart v.8.0 software .First, we investigated the effects of direct and observational conditioning with supra- and subliminal cue presentations. We compared subjects’ ratings to the moderately painful heat stimuli that were preceded by the different conditioned cues, both supraliminally and subliminally, using repeated measures ANOVA with factors cue (low vs. high), conditioning type  and awareness (conscious vs. non-conscious) and explored significant effects with pairwise comparisons  adjusted for multiple comparisons using p = 0.05  and awareness level (conscious and non-conscious). Four sets of planned comparisons: (1) direct conscious, (2) observational conscious, (3) direct non-conscious and (4) observational non-conscious were performed, using 1-tailed paired t-tests , conditioning type  and cue (high vs. low) as factors, as well as planned comparisons between high vs. low, high vs. neutral and low vs. neutral cues. We used this early (1–4 s) time window  for the conditioning test (phase 3) and for the extinction test (phase 5). We used a repeated measures ANOVA with the factors phase (conditioning test vs. extinction test), conditioning type  and awareness (conscious vs. non-conscious). = 5.136, p = 0.035, η2 = 0.213]; pain ratings to directly learned cues were higher (Mean ± SE: 51.6 ± 2.6) than to observationally learned cues (49.9 ± 2.6). Results also showed the main effect of cue  and an interaction of cue and awareness , indicating that the conditioning effects of both direct and observed cues were smaller with subliminal presentation (FDR < 0.001), observational conscious (pFDR = 0.001), direct non-conscious (pFDR = 0.019), observational non-conscious (pFDR = 0.012); see black asterisks in First, we compared subjects’ ratings to identical heat stimuli that were preceded by the respective cues presented subliminally or supraliminally using repeated measures ANOVA with factors: cue (low vs. high), conditioning type  and awareness (conscious vs. non-conscious). Ratings to the new neutral cue were not included in this analysis. Results revealed a main effect of conditioning type . There were larger skin conductance responses to directly (Mean ± SE: 0.22 ± 0.06), compared to observationally, learned cues. There were no significant differences between low and high cues or differences from the neutral cues during the test phase.We also examined skin conductance responses during conditioning and test phases . We focuThe repeated measures ANOVA for the SCR in the wider 1-6 s time window showed the main effect of awareness . Larger skin conductance responses were observed with supraliminal , compared to the subliminal (0.31 ± 0.07), presentations. No differences between cues or conditioning types were observed in this wider time window. = 34.641, p = 0.033, η2 = 0.217]. This suggests that while the differences between high and low cue responses were smaller for subliminal compared to supraliminal presentation, they were not different between conditioning types or phases  would affect direct/observational or conscious/non-conscious results differentially, we compared the initial test (phase 3) with the test (phase 5) following extinction , during r phases .We compared the effect of supraliminal and subliminal presentation of directly and observationally conditioned cues on pain perception. Although directly conditioned cues generally produced greater pain sensitivity as evidenced by larger skin conductance responses and higher pain ratings, the magnitude of the conditioning effect during test phases was similar for directly and observationally conditioned cues. Importantly, significant differences between low and high cues presented subliminally were observed for both directly and observationally conditioned cues. Our subliminal effects appeared to be modest but comparable to a recent study employing a similar direct conditioning paradigmStudies investigating autonomic responses to observational conditioning have found direct, compared to observational, learning to produce larger skin conductance responsesPrevious studies investigating non-conscious activation of directly and observationally conditioned cues used emotional stimuli (painful images or fearful faces)4The direct and observational conditioning effects persisted following extinction trials, suggesting that these conditioning effects are equally durable . The subAlthough the within-subject design allowed us to examine the effects of direct and observational learning within the same individual, it also meant that all subjects had experience with the direct conditioning paradigm, as direct and observational sessions alternated. The direct conditioning experience could have influenced observational learning, perhaps by making the experience of the model in the video easier to imagine. However, previous work has found that the effect of observational conditioning is attenuated following exposure to direct conditioning, rather than augmented22How to cite this article: Egorova, N. et al. Not seeing or feeling is still believing: conscious and non-conscious pain modulation after direct and observational learning. Sci. Rep.5, 16809; doi: 10.1038/srep16809 (2015).


However, limited information is available for underlying genetic architecture of longitudinal trend in EW. Herein, we measured EWs at nine time points from onset of laying to 60 week of age, and conducted comprehensive genome-wide association studies (GWAS) in 1,534 FNCAPG harbors a non-synonymous SNP (rs14491030) causing a valine-to-alanine amino-acid substitution. Genome partitioning analysis indicated a strong linear correlation between the variance explained by each chromosome and its length, which provided evidence that EW follows a highly polygenic nature of inheritance.Egg weights at all ages except the first egg weight (FEW) exhibited high SNP-based heritability estimates (0.47 ~ 0.60). Strong pair-wise genetic correlations (0.77 ~ 1.00) were found among all EWs. Nine separate univariate genome-wide screens suggested 73 signals showing significant associations with longitudinal EWs. After multivariate and conditional analyses, four variants on three chromosomes remained independent contributions. The minor alleles at two loci exerted consistent and positive substitution effects on EWs, and other two were negative. The four loci together accounted for 3.84 % of the phenotypic variance for FEW and 7.29 ~ 11.06 % for EWs from 32 to 60 week of age. We obtained five candidate genes, of which Identification of significant genetic causes that together implicate EWs at different ages will greatly advance our understanding of the genetic basis behind longitudinal EWs, and would be helpful to illuminate the future breeding direction on how to select desired egg size.The online version of this article (doi:10.1186/s12864-015-1945-y) contains supplementary material, which is available to authorized users. In poultry industry, egg weight has always been an economically important trait, and is usually regarded as the major breeding objective and research goal –4. As a http://www.animalgenome.org/cgi-bin/QTLdb/index). However, a majority of reported QTLs are mapped with wide confidence intervals by low-density linkage analysis in the past [Multiple lines of evidence have suggested that egg weights are mainly determined by genetic factors and they all show considerable heritability estimates , 10, 11.the past . In genethe past . To imprthe past , 15. So the past , 16. Recthe past . In chicDespite the great advantages of GWAS, most studies to date utilized only phenotypes measured at a single time point , 18–20. 2 chickens with observations for egg weights at different ages. In addition, we examined the genetic architecture of egg weight by partitioning genetic variation according to chromosome. The main goals of our current work were to assess the feasibility of longitudinal data as an intriguing resource in GWAS, pinpoint associated loci and genes that contribute to the phenotypic variability and longitudinal trend in egg weight, and provide valuable insights into the genetic basis of longitudinal egg weights.In the present study, we implemented univariate, multivariate and conditional GWASs using 600 K Affymetrix Chicken SNP array in a total of 1,534 Fhsnp2 = 0.60). Moreover, bivariate GCTA analyses indicated that egg weights at multiple ages were highly and positively interrelated, especially for egg weights at two neighboring time points. As the beginning of entire laying stage, FEW showed slightly lower genetic correlations with egg weights at the following ages (rg < 0.90), compared with those among egg weights from 32 to 60 week of age (rg > 0.90).Descriptive statistics for nine egg weight variables are presented in Table rs316497033 on GGA3). Of all significant association signals, 45 SNPs were responsible for only one trait and other 28 hits affected multiple phenotypes. In particular, four loci around rs14491030 were found to be implicated in all egg weights except FEW. The global view of the putative P-values for all SNPs affecting EW36 is given in Fig. 1000 values varied from 0.987 to 1.010. These results indicated negligible inflation of the observed genome-wide association signals caused by population stratification. Notably, moderate deviations within the upper tail of the distribution were found in all QQ plots, in spite of stringent quality control and inclusion of up to top five PCs. Thus, the departure due to a great number of weakly associated SNPs was indicative of polygenic inheritance.As a preliminary, we conducted nine separate association tests using univariate method for longitudinal egg weights. In total, 73 genome-wide significant SNPs located on chromosome 1, 3 and 4  were successfully identified for these nine traits  on GGA1, survived the genome-wide suggestive threshold of multivariate model. Considering that rs314058619 and rs14916609 are separated by 1.5 Mb and the pair-wise LD between them is relatively low at D’ = 0.37 and r2 = 0.09 (a LD block extends only for a short distance), we treated rs14916609 as another separate signal. Taken together, we obtained three significantly independent loci associated with all egg weights from multivariate analysis.In total, we obtained 270 genome-wide suggestive loci from nine independent univariate analyses. To enhance the statistical power, a joint GWAS analysis of nine traits was performed by fitting these SNPs into a multivariate model. Consequently, a total of seven significant hits on GGA1 and GGA4 provided compelling evidence for associations with longitudinal egg weights . After two-step univariate conditional tests on rs314058619 and rs14491030, the third SNP rs14916609 was still significantly associated with all traits except FEW. This locus seemed to have independent effects on these traits, despite that it showed only suggestive significance inferred by two-round multivariate conditional GWASs. The finding further strengthened the validity regarding rs14916609 as an independent hit. It should be noted that the significance levels of loci nearby the peak signals were substantially attenuated after adjusting for the three independent hits. In order to provide visual support of independent associations, we interrogated the signals in the 1.0 Mb genomic region surrounding the independent loci (500 kb each side). Since rs14916609 and rs14491030 affected more phenotypes, we illustrated their regional association plots for EW36 and EW60 to compare the difference of putative significance levels before . According to the putative SIFT score (0.74), the change of amino-acid was predicted as tolerated to protein structure and function.Gene annotation of the four significant SNPs allowed us to identify genes related to longitudinal egg weights. Considering that the putative variants may be in high LD with a causal locus genuinely associated with phenotype, we inferred the LD block around the sentinel SNP using Haploview. Four blocks containing the four hits were identified and the detailed information is summarized in Table 2 population, parameter estimates for some traits in the joint model could not converge. However, the strong genetic correlations between nine egg weight phenotypes provided evidence that they had great potential to share a consistent genetic architecture. Therefore, we only exemplified the partitioning spectrum of EW36 due to its highest heritability. The estimates of variance contributed by each chromosome exhibited a strong linear relationship with the length of the chromosome for EW36  on GGA1 are segregated by 1.5 Mb and located in the intronic regions of CAB39L  and FKHR , respectively. The CAB39L gene has been proposed to participate in the mTOR signaling pathway. It is increasingly apparent that mTOR signaling can affect most cellular functions as a central controller of cell growth (mass accumulation) and proliferation [FKHR is a member of FOXO subfamily and an important mediator of the insulin signaling pathway [In total, four LD blocks tagged by the resulting SNPs were inferred, and contained five candidate genes of potentially functional relevance. Two SNPs  located within the NCAPG  was unveiled in the current study. In chickens, many independent studies reported that multiple genomic segments containing this gene were identified to be implicated in both egg weight and body weight [CCKAR (cholecystokinin A receptor) located around 2.7 Mb away from NCAPG is mainly responsible for body weight [CCKAR might be a more promising causal gene. Notably, the gene NCAPG has been suggested to be associated with many growth and weight traits in several livestock species [NCAPG for body weight in chicken, owing to a particularly interactive relationship between egg weight and body weight [NCAPG gene may exert a pleiotropic effect involved in the two phenotypes simultaneously. Consequently, the impact on body weight of the gene for egg weight identified by us requires further investigation.A non-synonymous mutation rs4491030 ly weight , 20, 53.y weight , by estay weight , CCKAR m species –60. Thery weight , i.e., tCDADC1 (cytidine and dCMP deaminase domain containing 1) is located about 18.2 kb upstream of SNP rs14916609, but its function and mechanism is not yet clear. One previous study indicated that this gene may be an important factor regulating testicular development and spermatogenesis in human [KCNG3  indexed by rs316497033 encodes a subunit of the potassium voltage-gated channel. It is known to be mainly involved in cell volume and smooth muscle contraction [Another gene in human . Due to traction , and theNCAPG may influence both egg weight and body weight simultaneously in a pleiotropic manner. These promising loci and genes could be helpful to engineer practical breeding programs and produce the desired egg size according to diverse consumption markets.In summary, we performed univariate, multivariate and conditional GWASs for longitudinal egg weight data using high-density 600 K SNP arrays, and suggested that longitudinal analysis had higher power to dig out variants that influence phenotype variability over time. Our study provided evidence that egg weight appears to be highly heritable and polygenic, and shares the similar genetic determinants and mechanisms at different ages. Four significant loci and five candidate genes were detected with significant effect on egg weights. In particular, 2 resource population was developed by reciprocal crosses between White Leghorn (WL) and Dongxiang chickens (DX), representing a popular commercial breed and a Chinese indigenous strain, respectively. The two pure lines were maintained for about ten years at the experimental farm, and WL eggs weighed about 14 g more than DX eggs at the same age. Six WL males were mated with 133 DX females and six DX males were mated with 80 WL females, to generate 1,029 and 552 birds of the F1 generation, respectively. Then, 25 males and 407 females from WL/DX cross and 24 cocks and 235 hens from DX/WL cross were selected to produce the F2 population. A total of 3,749 F2 individuals  with full pedigrees originating from 590 full-sib families were created in the same hatch. The population was maintained in three-tier single-hen cages and reared in the same environment with feed and water ad libitum at the experimental farm of Jiangsu Institute of Poultry Science. Finally, to ensure sufficient phenotypic information and accurate pedigree, we chose 1,534 hens from 49 half-sib families and 550 full-sib families for SNP genotyping.An FTo characterize the genetic architecture of egg weight developmentally, we collected egg weight data at nine different time points. Firstly, the first egg weight (FEW) was recorded when hens started laying, mainly considering that FEW is conceptually defined as weight of first egg for each hen, and it is very difficult to collect eggs on several consecutive days due to the physiologically unstable state of hens at onset of laying. Subsequently, egg weights (EW) were measured on two consecutive days per four weeks from 32 to 60 week of age, and the average for two days was regarded as the phenotypic value for each hen. Cracked, soft-shell and double-yolk eggs were not used in our study. Descriptive statistics were calculated with the MEANS procedure of the SAS software package  using all available records. For traits deviating from normality, we conducted the rank-based inverse normal transformations (INTs) using SAS ahead of association tests . BrieflyP < 1 × 10−6 using the PLINK v1.90 package [R2 > 0.5 underwent the next analyses step. Finally, a total of 1,512 samples and 435,867 SNPs were eligible for inclusion in the following GWASs.The whole blood samples were collected from brachial veins of chickens by standard venipuncture. Genomic DNA was isolated using standard phenol/chloroform extraction method and genotyped with the 600 K Affymetrix Axiom Chicken Genotyping Array . From an initial set of 580,954 SNPs , 7,883 S package . Some sp package , then on--indep-pairwise 25 5 0.2 command (PLINK), and then calculated top five PCs as covariates into the mixed model. To establish proper thresholds for genome-wide suggestive and significant associations, we corrected for multiple testing using the simpleM method [eff = 59,308, thus the genome-wide suggestive and significant P-values were 1.69 × 10−5  and 8.43 × 10−7 , respectively.Prior to GWAS, we conducted a principal component analysis (PCA) to eliminate spurious associations due to the presence of potential cryptic relatedness or hidden population stratification. Considering that clusters of highly correlated SNPs may distort the resulting PCs, we first pruned the full SNP set to 41,130 independent SNPs via the M method  accounti10-transformed observed P-values were generated using the “gap” and “qqman” packages in R [We firstly performed univariate tests of association for SNPs having MAF ≥ 0.05 using an exact mixed model approach implemented in the GEMMA v0.94 software . The cenges in R , 70. We ges in R . Furtherges in R , 73. They is an n × 1 vector of phenotypic values for n individuals, W is an n × c matrix of covariates  including a column vector of 1, α is a c × 1 vector of corresponding coefficients including the intercept, x is an n × 1 vector of marker genotypes at the locus tested, β is the corresponding effect size of the marker and all effects are reported for the minor allele in each marker, u is an n × 1 vector of random polygenic effects with a covariance structure as u ∼ N, where K represents a known n × n genetic relatedness matrix derived from SNP markers and Vg is the polygenic additive variance, and ε is an n × 1 vector of random residuals with ε ∼ N, where I is an n × n identity matrix, and Ve is the residual variance component. We used the Wald test statistic β = 0, where the best linear unbiased estimate (BLUE) of β and the corresponding sampling variance g and Ve.for the equation , y is anTi2 is the estimated Wald statistic and asymptotically distributed as a chi-square with 1 degree of freedom under the null hypothesis, and usually called observed χ2 statistics, and 0.455 is the expected median of the standard χ2 distribution under the null hypothesis of no association. For the formula  is an n × c matrix of covariates  including a column of 1 s, A is a c by d matrix of corresponding coefficients including the intercept, x is an n-vector of marker genotypes, β is a d vector of marker effect sizes for the d phenotypes. It should be noted that G is an n by d matrix of random effects with G ~ MVNn×d where Vg is a d by d symmetric positive definite matrix of genetic variance component, and E is an n by d matrix of residual errors with E ~ MVNn×d where Ve is a d by d symmetric positive definite matrix of residual variance component (K and I are the same in the two models). MVNn×d denotes the n × d matrix normal distribution with mean 0, row covariance matrix V1 (n by n) and column covariance matrix V2 (d by d).where −4 and 7.59 × 10−6 through multiplying the raw thresholds by the number of phenotypes [Owing to the different number of statistic tests, we further adjusted the significance level in multivariate testing accounting for the nine independent inquiries in usual single-phenotype strategy. For the multivariate model, we corrected the genome-wide suggestive and significant cut-offs as 1.52 × 10enotypes .Notably, a genomic region containing a cluster of neighboring SNPs in strong LD is usually associated with a phenotype for high-density array. To demarcate independent association signals across the putative regions, we run stepwise conditional analyses both in multiple and single models, through fitting the genotypes  at the strongest signal identified by the multivariate analysis as covariates . The prohsnp2) for GWAS using the same inverse-normal transformed EW values. We also quantified the pair-wise genetic and phenotypic correlations among egg weights at multiple time points with the bivariate mixed model [For egg weight at each time point, univariate restricted maximum likelihood (REML) implemented in GCTA v1.24 program  was perfed model . A genety is an n × 1 vector of phenotypic values for n individuals, b is a vector of fixed effects with its incidence matrix X, gG is a vector of aggregate effects of all SNPs, and Var(gG) = AGσG2 with AG being the SNP-derived GRM and σG2 being the additive genetic variance, e is a random residual term with e ∼ N where σe2 represents the residual variance and I represents an identity matrix. In this model, we partitioned σG2 into the contributions of selected SNP loci  with all intermediate SNPs, but the intermediate SNPs are not necessarily in LD with each other. Subsequently, we performed functional annotation on the significant SNPs and searched for candidate genes in the blocks based on the Galgal4 assembly, using Variant Effect Predictor (VEP) and Biomart tools supported by Ensembl [In general, GWAS does not distinguish a genuine causal locus from those statistically significant loci within a strong LD region. Therefore, in order to characterize potential candidate genes responsible for a trait, we conducted LD analyses and inferred the haplotype blocks containing peak SNPs by Haploview v4.2 . A block Ensembl , 80.


This suggested that the random coiled form of DNA (−flow) reflected the DNA form in the bulk experiment in the case of DNA synthesis reactions. In addition, the DNA synthesis reaction rate of stretched ssλDNA (+flow) was approximately 75% higher than that of random coiled ssλDNA (−flow) (91 vs. 52 bases/s). The DNA synthesis reaction rate of the Klenow fragment (3′-5′exo–) was promoted by DNA stretching with buffer flow.Using a single-stranded region tracing system, single-molecule DNA synthesis reactions were directly observed in microflow channels. The direct single-molecule observations of DNA synthesis were labeled with a fusion protein consisting of the ssDNA-binding domain of a 70-kDa subunit of replication protein A and enhanced yellow fluorescent protein (RPA-YFP). Our method was suitable for measurement of DNA synthesis reaction rates with control of the ssλDNA form as stretched ssλDNA (+flow) and random coiled ssλDNA (−flow) via buffer flow. Sequentially captured photographs demonstrated that the synthesized region of an ssλDNA molecule monotonously increased with the reaction time. The DNA synthesis reaction rate of random coiled ssλDNA (−flow) was nearly the same as that measured in a previous ensemble molecule experiment (52  These results were the average of a large number of molecules. However, the real behavior of individual biomolecules and the elementary processes of the reactions have not been clarified. In fact, kinetic analysis of the elementary steps of DNA metabolic reactions, such as the binding rate, range of continuous DNA synthesis, and dissociation rate of DNA polymerases, remain insufficiently understood . Direct Escherichia coli DNA replication , 4 fmol of thiol-modified λDNA, and 100 pmol of 25-mer oligonucleotide. The reaction mixture was incubated according to the following heat denaturation program: 94 °C for 6 min, 58 °C for 1 min, and cooling to 4 °C. Detailed information of the preparation of thiol-modified λDNA is provided in our previous paper  containing 0.3 mM of each dNTP, 10% glycerol, 0.1% Tween 20, and 12.5 U of the Klenow fragment (3′-5′ exo–) was injected into the microflow channel until the entire chamber was uniformly filled with the buffer. Direct observation of the DNA synthesis reaction was preformed for both stretched ssλDNA and random coiled ssλDNA. The stretched ssλDNA molecules were observed under a flow rate of 25 μL/h. Fluorescent images were captured every 1 to 2 min. For random coiled ssλDNA, the buffer flow was transiently applied for a few seconds at a flow rate of 25 μL/h only when the fluorescent images of ssλDNA were captured. After completion of the DNA synthesis reaction, 0.3 μM SYTOX Orange  was injected into the microflow channel for 30 min to stain the double-stranded regions of λDNA, which were then visualized. Fluorescent images for both ssλDNA and dsλDNA were captured in the same microscopic field.Next, a DNA synthesis reaction buffer [50 mM NaCl, 10 mM Tris-HCl (pH 7.9), 10 mM MgCl3.Direct observation results of the DNA synthesis reaction by the Klenow fragment (3′-5′exo–) are shown in For one-end immobilized ssλDNA molecules, the white triangles and white arrows denote the positions of the immobilized end and free end, respectively. The single-stranded regions of the template λDNA molecule monotonously shortened during the DNA synthesis reaction. The DNA synthesis reaction was completed in 535 s under the stretched condition (+flow) . On the vs. 50 bases/s). This result suggested that the random coiled form of DNA (−flow) reflected the DNA form in the bulk experiment in the case of DNA synthesis reactions. Therefore, our single-molecule experiments were consistent with the DNA synthesis assay of ensemble molecules.Based on the number of bases/μm, the DNA synthesis reaction rate of the stretched ssλDNA (+flow) was estimated to be 91 bases/s. On the other hand, the DNA synthesis reaction rate of random coiled ssλDNA (−flow) was estimated to be 52 bases/s. It was reported that the DNA synthesis reaction rate of DNA polymerase I (Klenow fragment) was 50 bases/s in the assay of ensemble molecules . The DNAvs. 52 bases/s). This suggested that the DNA synthesis reaction rate was significantly promoted by higher DNA tension. The effects of tension on DNA metabolic reaction have been previously studied, e.g., the effects of template tension on DNA polymerase [We also compared the DNA synthesis reaction rates of stretched ssλDNA (+flow) and random coiled ssλDNA (−flow) at the single-molecule level. The DNA synthesis reaction rate of stretched ssλDNA (+flow) was approximately 75% higher than that of random coiled ssλDNA (−flow) . This result indicates that our single-molecule experiments were consistent with the assay of ensemble molecules, and our method can be applied to effects of DNA form on DNA synthesis reaction.In this study, we develop a new method to observe single-molecule DNA synthesis reactions in microflow channels, and applied to DNA synthesis by the Klenow fragment (3′-5′ exo–). The DNA synthesis reaction rates both for stretched ssλDNA (+flow) and random coiled ssλDNA (−flow) were successfully determined as 91 bases/s and 52 bases/s, respectively. The DNA synthesis reaction rate of random coiled ssλDNA (−flow) was almost the same as that measured in the ensemble molecule experiment (52


Both general and disease-related parenting stress were associated with a lower (DS)QoL , but not with HbA1c levels. Furthermore, with regard to the parent–child interaction, emotional involvement of parents  and expressed discomfort of the child  were related to suboptimal HbA1c levels. There was no clear pattern in the correlations between parent–child interaction and (DS)QoL.To test whether parenting stress and the quality of parent–child interaction were associated with glycemic control and quality of life (QoL) in young children (0–7 years) with type 1 diabetes (T1DM), we videotaped 77 families with a young child with T1DM during mealtime (including glucose monitoring and insulin administration). Parent–child interactions were scored with a specifically designed instrument. Questionnaires assessed general and disease-related parenting stress and (diabetes-specific (DS)) QoL. HbAConclusion: The results support the notion that diabetes does not only affect the child with T1DM: T1DM is a family disease, as parenting factors (like stress and parent–child interactions) are associated with important child outcomes. Therefore, it is important for health-care providers to not only focus on the child with T1DM, but also on the family system. In addior 7.5 % , 38 and or 7.5 % , 28. Des1c level , 41. Hav1c level ; therefoith T1DM . The litith T1DM , 49), whith T1DM , 31). A ith T1DM .1c level and QoL of the child.When young children are diagnosed with T1DM, parents have complete responsibility for the daily diabetes management  of their child , 42. Bec1c levels in school-aged children and adolescents (age range 7–17 years). From the same review, it appeared that in younger children (aged 0–11 years), parenting stress was not or even negatively associated with HbA1c levels, indicating that higher levels of stress were related to more optimal HbA1c levels [1c levels in parents of school-aged children and adolescents versus parents of young children could be due to the fact that parents of older children have a shared responsibility, while parents of younger children have a full responsibility for the care of their children with T1DM. Increased levels of parenting stress could indicate higher levels of involvement in the diabetes regimen and, therefore, more optimal HbA1c levels in young children [1c levels in young children, but not for child QoL [A recent review  has descc levels . This dichildren . The levchildren  only fouchildren . It is ihild QoL . Therefo1c levels , 591c lels e.g. , 56). In. In1c lels ls e.g. , 22) of  of 1c lels  with T1DM.Research examining the associations among parenting stress, parent–child interaction and child outcomes in young children with T1DM is scarce and urgently needed. More insight in this area may contribute to the development of new, effective interventions. Therefore, the present study was conducted to test whether, and how, parenting stress and the quality of parent–child interaction were related to the HbAn = 17) were excluded. Of the 121 eligible families, 77 families (64 %) agreed to participate. After receiving written informed consent, the mealtime situation (including glucose monitoring and insulin administration) was videotaped during a home visit  diagnosed with T1DM more than 6 months and their parents were recruited from 15 hospitals/institutions in the middle and southern part of the Netherlands . Parents who lacked basic proficiency in Dutch and children with an Autism Spectrum Disorder, Down syndrome and/or other mental disabilities . The hoThe first part of the questionnaire included items involving (socio)demographic characteristics  and clinical characteristics  and years since diagnosis).1c level) was determined at the hospital where the child was treated for T1DM and extracted from the medical records of the children, after receiving written consent from the parents. In clinical care, the HbA1c level is generally measured once every 2–3 months and gives an impression of the average blood glucose level over a 6- to 12-week period. Using the patient’s charts, we included the HbA1c level measured closest to the home visit (maximum of 3 months before or after the home visit).Glycemic control  was videotaped in all participating families during a home visit. The videotapes were scored by an observer (AN) with the qualitative OKI-DO observation instrument, which is specifically developed for children with T1DM, to assess the quality of parent–child interaction during diabetes-specific situations . This ob‘The caregiver receives this score if he/she fully determines what should happen without explaining anything to the child and with a visible lack of respect for the autonomy. For example, the caregiver just takes the finger of the child to check the glucose, (harshly) ‘pulls’ the child in the correct position to operate the insulin pump or determines (without consulting or warning the child) where and when the insulin injection takes place, the caregiver fully determines what and how much the child eats. If the child is (rather) independent in managing his/her diabetes, the caregiver receives this score if he/she repeatedly interferes when the child is managing his/her diabetes, while it is clear from the observation that the child can perform everything on its own’.To score 5: ‘The caregiver receives this score if he/she praises initiatives of the child and encourages the child to make decisions on his own regarding his/her diabetes. The child may, for example, read the glucose meter, operate the insulin pump or determine where and when the insulin injection takes place . Everything is determined in consultation with the child and the child is treated with respect.’Research shows encouraging indications for the usability, reliability and preliminary validity of the OKI-DO instrument to assess parent–child interaction in young children with T1DM during mealtime (including glucose monitoring and insulin administration) .α = 0.92). Higher scores reflect more general parenting stress. The 17-item version has shown good reliability [General parenting stress was assessed with the short Dutch version of the Parenting Stress Index , 12. Thiiability .frequency and difficulty. The scale scores were summed to get a total frequency (α = 0.93) and total difficulty score (α = 0.93). Higher scores reflect more frequency and difficulty in disease-related parenting stress. Adequate internal consistency and construct validity of the original version of the PIP have been reported [Disease-related parenting stress was assessed with a validated, 42-item self-report measure, the Pediatric Inventory for Parents (PIP) , 54. Parreported .α = 0.80) and five psychosocial-related scales: liveliness, positive mood, problem behavior, anxiety and social functioning , α = 0.75). The TACQOL includes 63 items constituting seven scales covering aspects of QoL: five health-related scales: pain and symptoms, motor function, autonomy, cognitive functioning and interaction with parents and peers , α = 0.94), and two psychosocial-related scales: experience of positive and negative emotions , α = 0.84). In both questionnaires, the parent indicates to what extent specific problems of the health-related functioning scales occurred in the past few weeks, with three response categories: ‘never’, ‘sometimes’ and ‘often’. If a problem occurs, the parents are asked how the child is feeling: ‘(very) good’, ‘not so good’, ‘pretty bad’, and ‘bad’. For each item, the two answers are combined into a single item score ranging from 0 to 4 (‘never’ 4 and ‘sometimes’ or ‘often’ combined with ‘(very) good’ 3, ‘not so good’ 2, ‘pretty bad’ 1, and ‘bad’ 0). With the psychosocial-related scales, the parents indicate on a Likert scale whether a certain emotion in their child has appeared in the last few weeks . Item scores for the psychosocial-related scales run from 0 to 2. All TAPQOL and TACQOL scales are linearly transformed to 0–100 scales; higher scores will correspond to a better QoL. Research showed that the TAPQOL and the TACQOL are reliable and valid questionnaires [Generic QoL was measured with the TNO-AZL Preschool Quality Of Life questionnaire or TAPQOL  in childonnaires , 19.α = 0.86). The originally child self-report questionnaire showed good reliability and validity [Diabetes-specific QoL (DSQoL) was measured with a child self-report questionnaire (Smiley Faces) for young children composed by the Hvidøre Study Group . This quvalidity .1c levels and (DS)QoL. Because different QoL questionnaires were used for children aged 0–5 and 6–7, we have examined the Pearson’s correlations for these questionnaires (generic and DS QoL) separately. The results of the correlations were considered statistically significant when p ≤ 0.05. Furthermore, the effect sizes were examined. According to Cohen, r of 0.10, 0.30 and 0.50 are considered as small, medium and large effects, respectively [Statistical analyses were conducted using the Statistical Package for the Social Sciences . Frequencies and descriptive statistics were used to present the (socio)demographic and diabetes-related characteristics of the participating families. Pearson’s correlation coefficients were calculated to examine the strength of the relationships between parenting stress and the parent–child interaction with HbA1c level of the children, measured closest to the home visit, was 59 mmol/mol or 7.6 % (range 32–80 mmol/mol or 5.1–9.5 %).Table Of the 77 observed parents (96 % mothers), 70 parents (96 % mothers) completed the questionnaire about general parenting stress and DSQoL of their child, 68 parents (96 % mothers) completed the questionnaire about the generic QoL of their child and 64 parents (94 % mothers) completed the questionnaire about disease-related parenting stress. Most of the 70 parents (96 % mothers) who completed the questionnaires were cohabiting or married/registered partners (7 % of the mothers and 0 % of the fathers were single). More than half of the participating mothers (54 %) had a higher educational level , while all fathers (100 %) had a Bachelor’s or Master’s degree .To assess the inter-rater reliability of the OKI-DO observations, a second observer (HvB) scored 20 % of the videotapes independently of the first observer (AN). The agreement with the first observer was high as weighted kappa was 0.73, indicating a good inter-rater reliability.1c level and (DS)QoL of the children.Table 1c level did not correlate significantly with general or disease-related parenting stress. These results indicate that elevated levels of both general and disease-related parenting stress were associated with lower (DS)QoL of young children with T1DM.Results showed that general and disease-related parenting stress were significantly negatively associated with both generic QoL  and diabetes-specific QoL . HbAemotional involvement  and child’s response to injection  were significantly positively associated with the Hba1c level of the child, which indicates that parents with children with higher HbA1c levels were more emotionally involved and that children with higher HbA1c levels expressed more discomfort during glucose monitoring . A better quality of instruction was associated with a better generic QoL in children aged 6–7 , and more emphasis on diabetes during the meal was significantly correlated with a better DSQoL in children aged 0–5 .Furthermore, only the OKI-DO domains 1c levels and (DS)QoL in young children with T1DM is still scarce. The present study focused on this youngest patient group and found that higher levels of (disease-related) parenting stress were associated with a lower (DS)QoL of the child and that emotional involvement and the child’s response to injection were associated with lower HbA1c levels.For health-care providers, maintaining or enhancing a good QoL of children with T1DM is as important as guarding or achieving good glycemic control . However1c levels. A previous study, however, concluded that higher levels of disease-related parenting stress were associated with more optimal HbA1c levels in young children with T1DM [1c levels. If there indeed is a significant association, appropriate interventions in order to lower disease-related parenting stress could be part of the treatment in lowering HbA1c levels.The results showed that parenting stress was not associated with HbAith T1DM . An explith T1DM  might beith T1DM , 45. In ith T1DM , none ofFurthermore, parents who experienced higher levels of (disease-related) parenting stress reported lower child QoL, especially DSQoL . This is in line with a study examining the associations between parenting stress and the QoL of teenagers with T1DM , but the1c level. Research with older children and adolescents with T1DM also showed that a suboptimal HbA1c level was positively associated with emotional involvement of the parents [1c level and thereby delaying the onset of long- and short-term complications [1c targets for their child because of fear of hypoglycemia [Parents were more emotionally involved when their child had a suboptimal HbA parents  and invo parents . Howeverications . Otherwiglycemia .1c level expressed more discomfort during glucose monitoring and/or insulin administration . Displaying more discomfort could be due to some form of needle phobia or a low pain threshold. When children experience needle phobia or have a low pain threshold, parents might postpone or omit insulin injections or glucose monitoring in order to avoid these stressful and unpleasant situations, which could result in suboptimal HbA1c levels [1c level might ‘worsen’ the diabetes for both parent and child, and that the child, due to an emphasis on their disease, experiences more discomfort during glucose monitoring and/or insulin administration.Furthermore, the results showed that children with a high HbAc levels . It coul1c level. Based on results of a previous study with young children [1c levels, we expected that, for example, less respect for autonomy or more negative behavior of the child would be associated with suboptimal HbA1c levels. This discrepancy in findings might be due to different sample characteristics, as our sample had more optimal HbA1c levels mmol/mol .The quality of parent–child interaction did not show clear patterns of correlations with (DS)QoL. Previous research with youth with T1DM showed that parent–child behaviors  were related to QoL , 24. TheThe present study has some limitations that need to be described. Research has shown that diabetes centers not only differ in structural issues, but also at an educational level and guidance regarding diabetes, which could influence glycemic control . BecauseA strength of the present study is the use of the OKI-DO instrument, as observations of “real-life” parent–child interactions and scored by an independent observer can provide more objective data to assess the quality of parent–child interaction than using self-report questionnaires or interviews . The OKIThe results of the present paper support the notion that diabetes does not only affect the child with T1DM: T1DM is a family disease, as parenting factors (like stress and parent–child interactions) are associated with important child outcomes. Therefore, it is important for health-care providers to not only focus on the child with T1DM, but also on the family system.


We recently demonstrated the specificity of surface-induced amyloidogenesis but the mechanisms of amyloidogenesis and more specifically of adsorption at hydrophobic-hydrophilic interfaces remain poorly understood. Thus, it is critical to determine how amyloidogenic polypeptides behave at interfaces. Here we used surface tensiometry, rheology and electron microscopy to demonstrate the complex dynamics of gelation by full-length human islet amyloid polypeptide (involved in type II diabetes) both in the bulk solution and at hydrophobic-hydrophilic interfaces (air-water interface and phospholipids). We show that the hydrogel consists of a 3D supramolecular network of fibrils. We also assessed the role of solvation and dissected the evolution over time of the assembly processes. Amyloid gelation could have important pathological consequences for membrane integrity and cellular functions.Many chronic degenerative diseases result from aggregation of misfolded polypeptides to form amyloids. Many amyloidogenic polypeptides are surfactants and their assembly can be catalysed by hydrophobic-hydrophilic interfaces (an air-water interface  The deposition of misfolded and aggregated polypeptides to form amyloids is the hallmark of an increasing number of degenerative diseases including Alzheimer’s disease (AD) and non-insulin dependent diabetes mellitus type II (NIDDM)Amyloidogenesis occurs via a nucleation-dependent polymerisation process, during which the rate-limiting step is the formation of nuclei due to an energetically unfavourable association of monomersAmyloidogenic polypeptides are surfactants due to their amphiphilicity5659in-vitro amyloidogenesis of IAPP and the AD amyloid-β peptide (Aβ) can be significantly promoted by an air-water interface 7111213in-vitro due to a dominant AWI effectin-vitro. Although the AWI is not as complex as membranes, it represents a very attractive HHI model due to its reproducibility and homogeneity. Thus, the dissection of the interfacial behaviour of amyloidogenic polypeptides can be achieved by using model HHIs such as the AWI. In turn, such studies can pave the way for investigations using more physiological and complex HHIs .The Many proteins adsorb at interfaces and form there multi-layered proteinaceous networks, which can be stabilised by gel formation. The gel layer itself can be stabilised by numerous non-covalent interactions to form a meshwork of aggregates (e.g. fibres), typical of amyloidogenic polypeptides. Gel formation has been reported for a range of classical amyloid or amyloid-like polypeptides, e.g. IAPP, α-synuclein and the RNA-binding protein fused in sarcoma415161718152021222324251–40, suggesting that viscoelasticity might be a generic property of amyloid peptides. To our knowledge this is the first full rheological characterisation of the dynamics of gelation by a full-length non-mutated pathological amyloid-forming polypeptide. This study serves as a stepping stone to understand the significance of the adsorption of amyloidogenic polypeptides at HHIs in a more physiological context, i.e. cellular membranes.In this paper, we investigated the physical properties of human IAPP assembly over time, along with its adsorption parameters in order to characterise key events that drive amyloid assembly. We studied IAPP adsorption at HHIs  using surface tension measurements, its viscoelastic properties using rheology  and its morphology using electron microscopy. Moreover, we assessed the role of solvation in both fibrillisation and gelation, showing that the kinetics of elongation of amyloid precursors and of gel formation can be dependent on IAPP interactions with solvent water. We also characterised the viscoelastic properties of a hydrogel formed by the AD Aβin-vitro to study IAPP (e.g. 4 μM), gelation had occurred after 24 hrs since inverting the tube resulted in the solution remaining at the bottom of the tube instead of falling into the cap. At 51.3 μM IAPP, macroscopic aggregates were visible in the gelled solution (left panel). The gel formed was quite fragile as it could be broken up by pipetting or shaking of the tube, as was previously observed for gels formed by tau2–19 and an Aβ16–2023Fig. 1a, middle panel). At higher magnification, individual amyloid fibrils, amyloid fibril bundles as well as supramolecular networks of condensed amyloid fibrils were clearly identifiable (right panel).An IAPP-based hexapeptide (NL6) was previously shown to form a hydrogel composed of fibrillar networksright panel). Subsequently, an oscillation displacement of 5 × 10−3 rads was selected to ensure that the moduli were independent of strain. We also ascertained that DMSO (the IAPP solvent) did not affect the measurements (left panel). From the start of the experiment, a sol-gel transition (G’ = G”) of 4 μM IAPP could be observed . Rapidly the storage modulus G’ (a measure of surface elasticity) dominated over the loss modulus G” (a measure of surface viscosity), indicating elastic and solid-like behaviour, i.e. rapid gelation of the IAPP solution. A distinct cross-over point of G’ and G” could not be observed. A frequency sweep performed at the end of the experiment showed that G’ dominated G” at all frequencies tested with the Tan value  between 0.14 and 0.38 . Both moduli also showed frequency independence. Altogether, these results are characteristic of the formation of a 3D hydrogel by the entire IAPP solution (bulk and AWI) resulting from a multilayer network structure with viscoelastic gel-like behaviour.We then characterised the viscoelastic properties of the IAPP gel by oscillatory rheology. Typically gels display a non-zero shear elasticity. Strain amplitude measurements were performed to establish the linear viscoelastic region (right panel). Both moduli also showed frequency independence. G’ reached plateau showing that gelation was complete at the end of our experiment.Formation of a 3D hydrogel was also observed for the full-length AD Aβleft panel and 2b; The gelation of IAPP showed complex dynamics with two distinct kinetic regimes identified from 6 independent experiments; a “slow” regime (3 independent experiments) taking ~2 hrs for both moduli to increase at rates of 0.28 (G’) and 0.08 (G”) Pa/hr, and a “fast” regime (3 independent experiments) taking ~0.5 hr with rates of 4.7 (G’) and 2.3 (G”) Pa/hr (2O for deuterium oxide (D2O). Deuterium atoms are twice as heavy as hydrogen atoms, therefore D2O is a less reactive molecule than H2O and deuterium bonds are stronger than hydrogen bonds. Exchanging H2O for D2O allows probing for importance of molecular interactions in aqueous solution.To study IAPP gelation in more detail, we substituted H2O, the kinetic variations for IAPP gelation were abolished. The system adopted a unique regime taking ~0.4 hr for both moduli to increase at rates of 4.6 (G’) and 1.3 (G”) Pa/hr (2O (2O. G” plateau was unchanged by the isotopic substitution (~0.75 Pa). G’ dominated G” at all frequencies tested with the Tan value between 0.07 and 0.21 and moduli again showing frequency independence (2O than in H2O.In D”) Pa/hr . The laga/hr  of the classical amyloid dye, thioflavin T (ThT)With D2O for D2O did not affect IAPP lag phase or plateau height (inset). Indeed, the coefficient of variation (standard deviation/mean) clearly shows that the elongation for the reactions in H2O is more variable than that of reactions in D2O. Thus, it is also clear that D2O reduced the variation in the elongation kinetics. Furthermore, the morphology of the species at the end of the fibrillisation reactions (i.e. when plateau was reached) was not discernibly different between H2O and D2O (left panels) with sections of individual fibrils visible (arrowheads right panels).Substituting Hu height . Howeveru height inset. I and D2O . Both reWe then assessed IAPP adsorption to the AWI by measuring surface activity . IAPP loinset in right panel) and an oscillation displacement of 5 × 10−3 rads was then used. We also ascertained that DMSO (the IAPP solvent) did not affect the measurements . The sol-gel transition (G’=G”) and gelation (G’ > G”) of 4 μM IAPP at the AWI were rapid (~0.5 hr). By 2 hrs, G’ started plateauing but the two moduli were still slightly increasing indicating that interfacial gelation had occurred but equilibrium was not reached at the end of the experiment. G’ values after 8 hrs were ~6.2 mN/m, which is in the range previously reported for interfacial gelation of β-casein, β-lactoglobulin and uropathogenic E. coli3031Fig. 3b, right panel). Both moduli also showed frequency independence. Altogether, these results are typical of the formation by IAPP of a hydrogel at the AWI, and its evolution for 8 hrs.Since amyloidogenesis can be significantly promoted by the AWI, we next characterised IAPP gelation at the AWI by interfacial shear rheology. This technique characterises the viscoelastic properties of proteins adsorbed at interfaces and can provide important detail on the structure of the interfacial layer. The linear viscoelastic region was established  and anionic dioleoylphosphatidylglycerol (DOPG), which represents the minimum membrane charge density allowing complete IAPP binding to lipids but also resembles the lipid ratio of the pancreatic islet cell membrane33, left panel). Both moduli also showed frequency independence. These results indicate that gelation critically depends on HHIs.We first ascertained that the liposomes did not affect the measurements . GelatioFig. 4a20–29, the viscoelastic properties of the gelation process have never been investigated1516Adsorption of amphiphilic amyloidogenic polypeptides to HHIs catalyses amyloidogenesis by increasing the effective peptide concentration and promoting β-sheet formation571112in-vitro AWI and physiological lipids. We have also demonstrated that IAPP forms a 3D supramolecular network of condensed amyloid fibrils and we believe these to be responsible for the gelation process. Thus, we propose that IAPP gel network would be non-covalently cross-linked through typical amyloid β-sheet interactions . We believe it is unlikely that gelation resulted only from fibril entanglement as substitution of H2O by D2O showed an effect on the kinetic regime, suggesting that at least hydrogen-bonding plays a role. Furthermore, it has been shown that gelation of β-lactoglobulin resulted from hydrophobic and van der Waals interactions between fibrils2122We have clearly showed gelation of IAPP both in the bulk solution and at HHIs, both the 2O, we clearly observed distinct kinetic regimes, “slow” and “fast”, which collapse into a single “fast” regime in D2O. We believe these variations in the speed of gelation to be genuine kinetic variations rather than arising from sample-to-sample variations between independent measurements, often typical of amyloid studies. Indeed, sample-to-sample variations would have generated a range of kinetics covering the spectrum between what we called the “slow” and “fast” regimes  rather than two distinct groupings, as we observed. The observed kinetic variation suggests the existence of multiple gelation pathways. This is unexpected for a macroscopic system in which the self-averaging effects of a large number of molecules should mask distinct kinetic ratesOur rheological data suggest gelation is the natural final state of amyloidogenesis under our experimental conditions. However in H2O (see below), showing a unique regime similar to the “fast” one in H2O without any kinetic variation, also support our hypothesis of IAPP phase separation preceding gelation. Indeed, phase separation kinetics of deutereous polymer have previously been shown to be faster than that of hydrogenous polymer2O. Protein solubility was also shown to be lower in D2O due a stronger hydrophobic effect (i.e. a stronger tendency for proteins to associate), which would be suggestive of the system separating into phases422O triggered decrease in protein solubility (or increase in aggregation) would also be consistent with a more favoured phase separation (i.e. initiated more quickly and the phase separated drops growing more rapidly and thus eliminating the co-existence of multiple drops in the system). In a finite system, this can lead to a decrease in stochastic variations, which may explain why the separate “fast” and “slow” kinetic regimes are not observed in D2O. To ascertain whether IAPP gelation occurs through phase separation would be worthy of further investigations that are beyond the scope of this study.What might explain the macroscopic stochastic variation we observed for IAPP gelation would be the system separating into phases? We hypothesise that the variation may result from phase separation, during which IAPP-rich droplets form due to hydrophobic interactions . Phase s193738392O for D2O in rheology experiments. No significant change in gel viscosity was observed in D2O, with the G” plateau identical to that in H2O. Importantly, we found an increase in viscoelastic properties with the G’ plateau nearly twice higher than that in H2O, indicating that a stronger and more rigid gel had formed. A similar rigidity and strength for gels in D2O has previously been observed for gelatin and κ-carrageenan, which was attributed to stronger intermolecular attractions in D2O, leading to an increase density of packing and a more extensive gel network41422O, the critical micellar concentration was also shown to be lower and therefore the rate of aggregation to be faster, leading to a higher number of aggregates at the end of gelation422O (see below), which in turn should lead to a faster and less variable kinetic of gelation. Indeed, our results suggest that the effect of D2O in accelerating kinetic and reducing variation is widespread as D2O affected both early (the elongation rate of fibrillisation) and late (gelation) stages. Our results imply that, during rapid gelation (“fast” regime), a hydrogen bonding network between IAPP and H2O molecules is not the most relevant stabilisation factor and that hydrogen bonding between IAPP aggregates are more important. Conversely, slower gelation (“slow” regime) may partly be supported by hydrogen bonding absent in D2O.A gel formed in an aqueous environment is called a hydrogel. Hydrogel are vulnerable to shear thinning by application of a force (e.g. pipetting), which decreases gel viscosity and forces the physical crosslinks to reorganise. These characteristics were met by the IAPP gel. In a hydrogel, water participates in hydrogen bonding through bridging of charged groups and acts as a bridging element maintaining gel structure. Thus to address the properties of the gel network, we substituted H2O should be to weaken IAPP solvation and strengthen hydrophobic interactions, which should increase aggregation422O accelerated the elongation rate of fibrillisation. The lack of effect of D2O on nucleation is not surprising as nuclei would mostly form from monomers adsorbed at the AWI and this would not depend on whether the solvent was H2O or D2O. This is consistent with the study by Chi et al. showing that Aβ assembly at the AWI is driven by hydrophobicity, and changes in solvent conditions (such as pH and ionic strength) had no effect2946462O for D2O. A higher concentration of monomers on the fibril surface generally leads to higher elongation rate2O should be more prevalent while the monomer concentration is high, like during elongation. Successful attachment of monomers to fibril ends would also require the solvent to be removed, which suggests that elongation should be slower in H2O than in D2O, as we indeed observed. Thus, D2O would increase hydrophobic interactions leading to faster monomer association onto fibrils and generally to faster elongation. Finally, the hydrophobic cluster of β2-microglobulin monomers was shown to become buried when monomers are transferred to fibril ends and before stabilisation occurs through hydrophobic and hydrogen interactions, which suggests that the system would again become solvent independent462O).We also investigated the importance of IAPP solvation in stages prior to gelation, i.e. fibrillisation. The main effect of Dinset of Some striking features were revealed when we analysed the evolution over time of IAPP adsorption, fibrillisation and gelation . Not onlA detailed characterisation of the viscoelastic properties of the gelation process of a full-length pathological amyloidogenic polypeptide has never been undertaken before. Our study has clearly demonstrated the complex dynamics of the formation by IAPP of a 3D hydrogel, consisting of a 3D supramolecular network of condensed amyloid fibrils. We also showed the formation of a 2D physical gel at HHIs. Furthermore, we demonstrated the critical importance for gelation of the presence of an HHI, either AWI or physiological phospholipids, as increasing the HHI surface area accelerated the kinetics. We previously showed that both amyloid precursors (pre-fibrillar) and fibrillar species strongly adsorb at the AWI, with the fibrillar assembly adsorbing more strongly than precursors415161718192021222324251–40 (EZBiolab) were purchased already purified by reverse-phase high performance liquid chromatography. Both peptides were resuspended in DMSO (IAPP at 512.4 μM and Aβ1–40 at 1.6 mM), sonicated and centrifuged for 1 hr at 15,000 g at +4 °C prior to use (to remove any pre-aggregated species). DMSO was used to maintain the peptides in a monomeric pool lacking any β-sheet secondary structuresLyophilised synthetic human IAPP (Bachem) and AβChloroform stocks of DOPC and DOPG (Avanti Polar Lipids) were mixed in a 7:3 molar ratio. After solvent evaporation and desiccation, the lipids were hydrated in water and extruded through 0.1 μm pore size filter (Whatman). The number of liposomes was assessed with a NanoSight LM10 apparatus .The surface tension of 4 μM IAPP (from the DMSO stock solution) in water was measured at 21.8 °C by pendant drop shape analysis using a ‘Tracker’ video enhanced drop tensiometer (ITConcept), as previously described51.3 μM IAPP (from the DMSO stock solution) in PBS in a 200 μl reaction volume was left to fibrilise at room temperature in a quartz cuvette. The macroscopic aggregates at the AWI were pipetted out, deposited on a coverslip and then on a sample holder using conductive tape, dehydrated with increasing percentages of ethanol, dried with hexamethyldisilazane, sputtered with ~7 nm gold before being examined with a Zeiss NVision 50 microscope using an accelerating voltage of 2 kV.1–40 (from the DMSO stock solution) was pipetted onto the lower plate of the rheometer and water or D2O (Sigma-Aldrich) was added to get a 1.4 ml reaction volume and a 4 μM IAPP or 30 μM Aβ1–40 final concentration. Liposomes at a 4 μM final concentration  were also added when required. Then the upper plate  was lowered as slowly as possible onto the sample to ensure a completely filled gap. An environmental cuff with moistened tissue inside was placed around the geometry to prevent sample dehydration. Controls containing DMSO with or without liposomes were also performed. Oscillation time sweeps were recorded with a controlled displacement of 5 × 10−3 rads and a frequency of 0.5 Hz. Frequency sweeps were also performed. Statistical analysis was performed with the two-sample t-test. For IAPP in absence of liposomes, 6 independent experiments were performed; for IAPP in presence of liposomes, 5 independent experiments were performed.Measurements were performed, at 25 °C, on a Bohlin Gemini 200 HR Nano rheometer . IAPP or Aβ2O or D2O. ThT fluorescence  was measured at 37 °C on a BMG Polarstar plate reader (BMG labtech) using a bottom-bottom configuration . The values of control wells (buffers without peptide) were subtracted from the values of test wells (peptide). The lag phase was obtained from the intercept on the time axis of the line formed tangent to the inflection point. The elongation rate was obtained from the slope at the inflection point of the sigmoidal curve and the plateau height from an average of the highest curve values attained at the end of the experiment. At least three independent assays, with at least 9 wells per replicate, were performed and analysed with the two-sample t-test.4 μM IAPP were dispensed in a 96-well plate  with 32 μM ThT in PBS, in a 100 μl final solution volume in H−3 rads and a frequency of 0.5 Hz. Frequency sweeps were also performed.Measurements were performed, at 25 °C, on a DHR-2 interfacial rheometer (TA Instruments) using a double wall ring and an 18 ml reaction volume. IAPP (from the DMSO stock solution) was pipetted at the bottom of the vessel and water was then added to give a 4 μM IAPP final concentration. Control containing DMSO was also performed. Oscillation time sweeps were recorded with a controlled displacement of 5 × 10How to cite this article: Jean, L. et al. Dynamics of the formation of a hydrogel by a pathogenic amyloid peptide: islet amyloid polypeptide. Sci. Rep.6, 32124; doi: 10.1038/srep32124 (2016).