Tumours are made up of a mixed population of different types of cells that include normal structures as well as ones associated with the malignancy, and there are multiple interactions between the malignant cells and the local microenvironment. These intercellular interactions, modulated by the microenvironment, effect tumour progression and represent a largely under-appreciated therapeutic target. We use observations of primary tumour biology from prostate cancer to extrapolate a mathematical model. Specifically, it has been observed that in prostate cancer three disparate cellular outcomes predominate: (i) the tumour remains well differentiated and clinically indolent – in this case the local stromal cells may act to restrain the growth of the cancer; (ii) early in its genesis the tumour acquires a highly malignant phenotype, growing rapidly and displacing the original stromal population  – these less common aggressive tumours are relatively independent of the local microenvironment and (iii) the tumour co-opts the local stroma – taking on a classic stromagenic phenotype where interactions with the local microenvironment are critical to the cancer growth.We present an evolutionary game theoretical construct that models the influence of tumour–stroma interactions in driving these outcomes. We consider three characteristic and distinct cellular populations: stromal cells, tumour cells that are self-reliant in terms of microenvironmental factors and tumour cells that depend on the environment for resources, but can also co-opt stroma.Using evolutionary game theory we explore a number of different scenarios that elucidate the impact of tumour–stromal interactions on the dynamics of prostate cancer growth and progression, and how different treatments in the metastatic setting can affect different types of tumours.The tumour microenvironment has a crucial role in selecting the traits of the tumour cells that will determine prostate cancer progression. Equally important treatments like hormone therapy affect the selection of these cancer phenotypes making it very important to understand how they impact prostate cancer's somatic evolution. When detected early, prostate cancer is a largely curable entity. Once metastatic, like many cancers, cure becomes impossible and the only option left is a strategy of chronic disease management. Metastatic prostate cancer is initially managed with therapies aimed at ablating endogenous androgen production, a strategy that deprives cells of growth-signalling factors. In addition, bisphosphonates or RANK ligand inhibitors disrupt tumour–stroma interactions in the bone and are routinely considered as part of the standard of care for metastatic diseases  model that studies the evolution of three different cell populations over time: stromal cells, a dependant tumour phenotype capable of co-opting stromal cells to support its growth, and an independent tumour phenotype that does not require microenvironmental support, be it stromal associated or not. This model is then applied to the clinical problem of metastatic prostate cancer.In EGT, the behaviour of the players is not assumed to be based on rational payoff maximisation, but it is shaped by trial and error adaptation through natural selection . In EGT,Genetic and epigenetic changes can transform the cells in a healthy tissue. One change is to produce individualistic tumour cells that compete for space and resources , includiAs in our previous work . The payγ), where γ represents the fitness cost for I cells to be independent, instead of committing those resources to faster proliferation. The D cells rely more on their microenvironment for survival and growth at a fitness cost (β) that represents the scarcity of resources or space that I cells can procure themselves. A resource-poor microenvironment would then be characterised by a higher value of β. As I cells produce space and shareable growth factors, this model assumes that D cells derive a fitness advantage from their interactions with I cells represented by the variable ρ. On the other hand, D cells interacting with other D cells will have a harder time sharing existing microenvironmental resources with other equally dependant cells and thus are assumed to have double the cost 2β for relying on the microenvironment for survival and growth and thus have a fitness of 1–2β.The I cells are relatively independent from the microenvironment and produce their own growth factors (e.g. testosterone) and thus are considered to have a comparatively constant fitness  or on the other hand being independent (γ) affect the outcome of prostate cancer.A key development from our previous work , W(I), W(D)) will be given by the following expressions:If pThe average fitness t will depend not only on its own fitness (W) but also on the fitness of the other cell populations. If the fitness of a phenotype X, W(X) is higher than the average fitness of all the phenotypes combined <W> then the proportion of that phenotype will increase during the next time step, for as long as the reasons that keep the phenotype relatively fit remain. The replicator equations are:From these expressions it is possible to derive the discrete replicator equations that describe how they change over time . The proα, the mutual benefit between D cells and co-opted stroma; ρ, the benefit that D cells derive from coexisting with I cells (which can produce growth factors and space); β, the fitness cost of relying on a microenvironment that might not be able to produce resources that I cells can produce on its own and γ, the cost that I cells have to incur to become independent from the microenvironment.One may apply the replicator equations described in the previous section to study the temporal evolution of the different populations in a number of scenarios. These scenarios are characterised by the four variables of the model: β=0.2, 0.5 and 0.8). In each case, the replicator equation was iterated 20 times from an initial condition assuming that both tumour populations represented a very small proportion, each 10−4 of the population, with the rest being stromal cells (S). We assumed that each of the tumour populations is equally likely of arising from the normal epithelial population (not modelled) as there is no conclusive evidence of one of the abnormal ones necessarily arising from the other (e.g.: I cells appearing as mutant D cells or vice versa). Different initial conditions yield similar results although the time required to reach equilibrium depends on the proportion of tumour cells in the population. We chose 20 time steps, as it appears to be sufficient for most simulations to reach stability , the main outcomes are either coexistence of tumour phenotypes or, when α or ρ is high (increasing the fitness of the D population), coexistence of the three phenotypes. The second row shows the outcomes from three scenarios characterised by different costs of relying on the microenvironment with an I phenotype with γ=0.5. When the microenvironment is rich in resources the main outcomes are either dominance of D phenotypes or, when γ is sufficiently high, coexistence of D and S.The first row in α is sufficiently small or coexistence of I and stroma if α is high enough. Interestingly for some values of α (from medium to intermediate-high), the outcome tends to be coexistence of the three phenotypes. For environments poor in resources (β=0.8) the main outcomes are driven by ρ, with low values of ρ (benefit for D cells coexisting with I cells) leading to dominance of I phenotypes and higher ones leading to coexistence of both tumour phenotypes.When resources are neither scarce nor plentiful the main outcomes are coexistence of I and D if γ=0.8, representing a relatively unfit I population. When the microenvironment is rich in resources the main outcomes are either dominance of D phenotypes or, when α is sufficiently high, coexistence of D and S. When resources are neither scarce nor plentiful the main outcomes are coexistence of I and D if α is sufficiently small or coexistence of D and S if α is high enough. Perhaps the most dynamically interesting and biologically relevant simulation is when the microenvironment is poor in resources (β=0.8) and the cost of being independent is high (γ=0.8) as shown in the bottom right corner of The third row shows the outcomes from three scenarios characterised by different costs of relying on the microenvironment with an I phenotype with ρ and α are low then the tumour will be dominated by I phenotypes. If α is 0.5 or below, a sufficiently high value of ρ leads to tumours that contain both I and D cells. When α is higher than 0.5 the cooperation between stroma and D results in the extinction of I cells. Coexistence between the three phenotypes occurs when ρ is high (which helps the D cells) and α is below 0.5 but not too low (over 0.3), which promotes cooperation between D and stromal cells without driving I cells to extinction.If both vs those independent of stroma is of great interest, the dynamics of these outcomes were explored in more detail. γ) or D phenotypes  could result in large changes in the population dynamics leading to fundamentally different outcomes. Left panel: a sufficiently high value of α and low value of ρ means that D cells derive a much higher benefit from their cooperation with stromal cells than from their interactions with I cells. Given the low general fitness of the I cells (with γ=0.8), it is not surprising that they quickly become extinct as the advantage of cooperation sustains, and promotes D and S cells in the tumour. The right panel in the same figure shows a slightly fitter I phenotype (with γ=0.75 instead of 0.8); the I population manages to sustain growth and, as it becomes an increasingly larger part of the tumour population, disrupts the already initiated cooperation between D and S cells, resulting in the extinction of the stromal population and a D population that represents a smaller part of the tumour compared with the previous example.As the emergence of stromagenic tumours vice versa. The replicator equations are initially iterated to form a stromagenic tumour (as in the left panel of β from 0.8 to 0.9). This results in a destabilisation of the cooperation between the D and S populations, and a state transition to the one exhibiting dominance of the I subpopulation.Changes in the microenvironment can occur during tumour progression both as a result of external intervention (e.g. treatment) and as a result of the tumour itself. From the results presented in I has already dominated) only causes a small shift. This result can be seen as an application of the kairos principle and speaks to the importance of choosing the right therapy at the right time. Testing this same concept in a more stromal-targeted therapy  did not produce significant differences, suggesting that a short delay in onset is of less importance in this therapeutic strategy. This result does not suggest that early vs late hormone therapy is meaningless – in fact it has been shown that early hormone therapy can slightly increase overall survival, but instead that the timing will not effect the overall outcome of the game.An exploration of a putative biological therapeutic agent with different timing strategies is represented in α will be reduced). This results in a shift in the opposite direction from the prior therapy – from D to I. Further, we see that the duration of therapy strongly affects the end result of the game. The final result  or by co-opting certain stromal cells in order to sustain tumour progression (as happens in bony metastatic disease). We present the simplest model that abstracts key aspects of prostate cancer evolutionary dynamics, including progression towards lethal outcomes that can be either stromagenic  or stromal independent. These outcomes reflecting evolutionary changes of the genetically unstable, heterogenous tumour cell population, are influenced by the interactions both between the different populations  and with their microenvironment. Primary tumours are likely to contain areas that are stromagenic as well as other areas that are stromal independent, which would make application of the therapeutical message of this model less relevant. On the other hand, secondary sites are thought to represent clonal populations originating from a specific  area of the primary tumour (γ), an increase in the proportion of I cells is observed as the microenvironment becomes resource-poor  in the treatment of metastatic prostate cancer, many physicians have adopted non-standard dosing schedules for their androgen ablation therapies. A recent study suggested that either using the patient's measured testosterone levels as a guide, or using an intermittent schedule as opposed to constant dosing  slowed the onset of castrate resistance  results These results, taken together, suggest that different therapies are likely of different value to the two major tumour types: D tumours are likely best treated with stromal manipulation  whereas I tumours would be better treated initially with a biological agent such as an mTOR inhibitor.Regardless of timing and schedule, the emergence of castrate resistance is largely unavoidable given a long enough time frame, and these results suggest that when this emergency does occur, a treatment strategy change is in order. These sentiments are echoed in the recent literature which suggests that the addition of mTOR inhibitors to hormone therapy after the onset of castrate resistance , but highlight the importance of understanding tumour–stroma interactions in driving not only tumour outcomes  but also their impact on potentially new therapeutic approaches. We have explored vast parts of the parameter space, so we are confident that these results capture the essence of our prostate cancer model. We made an assumption that the biology of metastatic sites is related to the original biology of the primary tumour. While this assumption carries with it many other assumptions, it is the one that underlies the majority of clinical decision-making and biological extrapolation in prostate cancer.Our model provides a theoretical framework to understand clinical observations. It is not intended to provide qualitative recommendations for timing and duration of therapy (limited by the arbitrary nature of the time variable in this model). However, this model suggests a number of testable hypotheses. It highlights the importance of the stromal cells in selecting for specific tumour cell phenotypes. It shows that stromagenic tumours are possible (as shown by the results where the steady state is made of S and D types). Importantly the results suggest that coexistence of microenvironmental dependant cells and the stroma is not always robust, and that changes like those resulting from a targeted therapy could transform the tumour into the more aggressive stromal-independent kind.The power of an abstract model such as this is not necessarily the direct interpretation of results, as many of the parameters tested are, as of yet, not biologically testable or actionable – but instead the method itself for testing new therapeutic strategies. In the clinical paradigm of metastatic prostate cancer, which has recently been muddied with many new agents coming to the arena, it has become ever more important to develop rational strategies to test new sequence and timing regimens. For example, it may be that the time-honoured standard of hormonal manipulation until failure is no longer the best strategy – but how can we ethically and rationally integrate these new therapies without some guidance? The results of this model suggest that with the multi-disciplinary effort of biologists, clinicians and theoreticians, rational strategies can be suggested from the morass of heretofore untested permutations of these new agents. We do not believe that the results presented in this paper are the final answer to the prostate cancer question, but instead hope that they begin conversations between disciplines and stimulate new kinds of questions.


Previous studies have shown that estimations of the calorie content of an unhealthy main meal food tend to be lower when the food is shown alongside a healthy item (e.g. fruit or vegetables) than when shown alone. This effect has been called the negative calorie illusion and has been attributed to averaging the unhealthy (vice) and healthy (virtue) foods leading to increased perceived healthiness and reduced calorie estimates. The current study aimed to replicate and extend these findings to test the hypothesized mediating effect of ratings of healthiness of foods on calorie estimates.In three online studies, participants were invited to make calorie estimates of combinations of foods. Healthiness ratings of the food were also assessed.The first two studies failed to replicate the negative calorie illusion. In a final study, the use of a reference food, closely following a procedure from a previously published study, did elicit a negative calorie illusion. No evidence was found for a mediating role of healthiness estimates.The negative calorie illusion appears to be a function of the contrast between a food being judged and a reference, supporting the hypothesis that the negative calorie illusion arises from the use of a reference-dependent anchoring and adjustment heuristic and not from an ‘averaging’ effect, as initially proposed. This finding is consistent with existing data on sequential calorie estimates, and highlights a significant impact of the order in which foods are viewed on how foods are evaluated. Reducing calorie intake is a critical component of successful weight loss, and individuals needing to lose weight are frequently advised to do so by focusing on their calorie intake. This is facilitated when food packaging includes calorie-content information, but in the large number of situations when no calorie labeling is available, individuals must make an estimate of the calorie content of the food when making a choice, subject to imperfect knowledge and a range of perceptual biases.A recent set of studies has highlighted one scenario where calorie content is systematically underestimated: Chernev The authors suggest it is the virtuous nature of the celery that drives this underestimate of the food’s energy content. The perceived healthiness of the virtuous food is averaged with that of the vice food, and leads to the meal as a whole being regarded as more healthy than the main meal alone. Because healthier foods are less likely to promote weight gain, they are also assumed to contain fewer calories This finding has important implications for public policy in the context of the current obesity epidemic. Incidental healthy foods, such as fruit and vegetables, are estimated to be used in 30% of advertisements for ‘energy dense nutrition poor’ foods The current study sought firstly to replicate the negative calorie illusion using methods that matched as closely as possible those used in previous studies https://requester.mturk.com/, 301 participants, all residents of the United States of America and aged over 18 years, were recruited via an online panel  was shown the main meal items alone, one group (n = 99) was shown the same main meal items with a green healthy side dish, and the third group (n = 98) was shown the same main meal items with a red healthy side dish. The main meals used in this experiment were : Cheeseburger , and meat lasagna  see .Each meal presentation included a visual image of a food and a written description. The choice of the stimuli is consistent with prior research Following calorie estimation, participants were presented with the same two foods again, and asked to rate the healthiness of the food on a five-point scale: “To what extent does this food fit with a healthy diet?” .It was decided to keep the phrasing of both the calorie estimate and the healthiness questions constant across all participants, even though some participants viewed images of one food item and others viewed images of two food items. Hence, both questions refer to ‘this food’, a term that directs participants to consider all the foods present in the image and is neither singular nor plural.Following this, participants were asked to provide additional measures of weight concern using “To what extent are you concerned with managing your weight?”  Analysis of variance was planned on calorie estimates and health estimates, with a main effect of the side dish and a main effect of main meal. If a significant effect of the side dish was found, the strength of the health estimates as mediators for the calorie estimates was then assessed.The nature of calorie estimates made it likely that the data were not normally distributed. This is because calorie estimates cannot be negative, so there was a lower bound to the possible estimates –zero – but no upper bound. As a result, the range of possible values for under-estimates was smaller than the range of possible values for over-estimates, which generates a positively skewed distribution. The presence of a normal distribution is important for the use of the proposed statistical analyses, so if the data are found to be positively skewed, a log-transform may be required prior to analysis.Previous studies using calorie estimates did not comment on the distribution of the data or the use of a transformation to correct for a non-normal distribution All participants gave a calorie estimate and healthiness estimate for both the burger and the lasagna. Potential effects of order were first assessed using analysis of variance, with a two-factor model . No effect of order  = 0.369, p = 0.55) or interaction between order and main meal  = 1.712, p = 0.19) was found on calorie estimates. A similar analysis of healthiness scores indicated no effect of order  = 0.56, p = 0.46) or interaction between order and main meal  = 3.154, p = 0.053). All following analyses therefore combine data from both trials.Participants judged the main meal alone to have on average 678 calories, while the main with the green side was believed to have on average 616 calories and the main with the red side was believed to have 620 calories see . AnalysiVisual inspection of a histogram of the calorie estimates revealed that they are positively skewed . The conAn alternative process to analyzing such data is to exclude data from participants that completed the task unusually quickly, suggesting poor engagement, and to exclude outliers (more than 2 standard deviations from the mean). Participants took on average 328 seconds (s.d. 217 second) and at least 128 seconds to complete the task, suggesting all engaged with the task to a similar extent. In terms of calorie estimates, three participants gave outlier estimates for the Burger , eight participants gave outlier estimates for the lasagna  and six participants gave outlier estimates for both foods. The remaining 284 participants judged the main meal alone to have on average 606 calories, while the main with the green side was believed to have on average 579 calories and the main with the red side was believed to have 586 calories. Analysis of variance of the raw calorie estimate data revealed no significant effect of main meal being assessed  = 2.678, p = 0.10) and no significant effect of the side on the calorie estimates  = 0.935, p = 0.39).Analysis of variance of the healthiness rating of the food revealed a significant effect of main meal being assessed  = 21.658, p<0.001), with lasagna rated as more healthy than the cheeseburger and no significant effect of the side on healthiness ratings  = 1.127, p = 0.32).Chernev Instead, weight concern as a between-participant factor with 5 levels was included as an additional factor in the analysis of variance of the natural log transformed data. No significant effect of weight concern were found either as a main effect  = 1.45, p = 0.22), or in an interaction with main meal  = 0.379, p = 0.84), with side dish  = 1.125, p = 0.34), or in a 3-way interaction  = 0.164, p = 0.99).When raw calorie estimates were considered, the analysis showed no significant effect of the side dish on calories estimates although the data showed a pattern in agreement with previous findings We found no increase in calorie estimates for the main with the side relative to the main meal alone despite more food being present. However, the actual calorie contents of these foods should be born in mind. A cheeseburger or a portion of lasagna will contain about 500 kilocalories, whereas a small apple or a small carrot (40 g) might only contain 20 to 60 kilocalories. Given the variance of calories estimates, the current study is unlikely to be able to detect an increase in calorie estimates of this magnitude.It is of note that there were significant effects of the main dish on healthiness ratings but not on the calorie estimates, suggesting that health ratings did not necessarily determine calorie estimates, as has been assumed by Chernev and colleagues This study failed to replicate the negative calorie illusion shown in previous studies The number of participants in Study 1 (301 participants in 3 groups) is sufficient to detect the effect size observed in one of the previous demonstrations of the negative calorie illusion: Chernev et al Another consideration is that the characteristics of participants in the current study differed from those in previous studies. Chernev 2(4) = 11.08, p<0.05), with Study 1 involving a lower proportion of individuals reporting high levels of concern, and a higher proportion of individual reporting a low level of concern. However, it should also be born in mind that the original demonstrations find a negative calorie illusion in calorie estimates across all participants, and not just those with high weight concern. It therefore seems unlikely that a difference in weight concern amongst study participants alone can explain the failure to replicate the negative calorie illusion.While the actual number of participants expressing each level of concern is not reported in Chernev Chernev and Gal argued that people perceived a meal combining a virtue and vice as being healthier than the vice alone Therefore, in Study 2, in addition to asking for calorie and healthiness estimates for a main meal alone, and a main meal with a healthy side dish, estimates were collected for the calorie content of the same main meal with an unhealthy side dish https://requester.mturk.com/, 541 participants, all residents of United States of America and over 18 years, were recruited via an online panel , with a small portion of a healthy side (n = 105), with a large portion of a healthy side (n = 108), with a small portion of an unhealthy side (n = 97) or with a large portion of an unhealthy side (n = 111). The main meal used in this experiment was a cheeseburger, served either with celery sticks  or French fries , in either small or large portions see . The smaThe testing procedure was exactly that same as for Study 1, with all the same measures taken in the same manner.Analyses of variance were planned on calorie and healthiness estimates. These were run separately for meals with the healthy and the unhealthy side and assessed a main effect of the side dish portion size on calorie estimates. Where a significant effect of the side dish was found, the strength of the health estimates as mediators for the calorie estimates was assessed by running a linear regression model, both with and without healthiness estimates in the model. If the inclusion of healthiness estimates in the model reduces the effect size for the side dish, healthiness estimates can be said to mediate the effect.Participants judged the main alone to have on average 6.35 ln calories . The same main with a small portion of a healthy side was judged to have 6.50 ln calories  and with a large portion of a healthy side to have 6.34 ln calories . Analysis of variance of the log-transformed calorie estimates data with the healthy side revealed a non-significant effect of the healthy side on the calorie estimates  = 2.172, p = 0.12) 2.By contrast, participants judged the same main with a small portion of an unhealthy side to have 6.66 ln calories  and with a large portion of an unhealthy side to have 6.73 ln calories . Analysis of variance of the log-transformed calories estimates with the unhealthy side data revealed a significant effect of the unhealthy side on the calorie estimates  = 14.2,p<0.001) 2. A posSince these data have shown a significant effect of the side dish on the calorie estimates, it was possible to assess the mediating effect of healthiness estimates on calorie estimates. As the small and large portions of side dishes did not yield significantly different calorie assessments, these were combined. The effect-size of side dish on calorie estimates in a linear regression model was compared with the effect-size when healthiness scores were included in the model. If healthiness scores acted as a mediator, the effect-size should fall with the inclusion of health scores.This analysis revealed that the inclusion of healthiness estimates into the model actually increased the effect size. The effect of both side dishes on calorie estimates were to increase these estimates, the healthy side by 6.3% (p = 0.38) and the unhealthy side by 36.9% (p<0.001). Including healthiness scores into the model made little difference to the effect-size of side dish on calorie estimates and in both instances increased it – the healthy side to 16.3% (p = 0.03) and the unhealthy side to 37.3% (p<0.001). This finding suggests that healthiness scores, as measured by an explicit rating scale, were not acting as a mediator for calorie estimates, failing to support the hypothesis proposed by Chernev The findings from Study 2 demonstrate that participants estimating a main with an unhealthy side had more calories than the main alone. It is of interest to note that this increase in calorie estimates did not show sensitivity to portion size. This is in keeping with the literature on categorization of foods which shows that individuals are insensitive to quantity, even for nutrients when very low levels are essential for health while high levels are damaging, such as salt It is also of interest to note that participants did not seem to be using a judgment of healthiness as a mediator for making calorie estimates. This fails to support the main explanation of calorie estimate effect proposed by Chernev, that “people rely on their evaluations of a meal’s overall healthiness to infer its calorie content” Study 2 provided a second failure to replicate the negative calorie illusion. This raises the question of how robust this finding is, and whether it can be explained by any protocol differences between the current study and previously published accounts The results of studies 1 and 2 provoked an important and unanticipated question: why did we fail to demonstrate the previously-demonstrated negative calorie illusion? A number of possibilities could be considered, including differences in the characteristics of the stimuli used or the participants recruited. It should be noted that Study 2 did partially replicate the findings from one of Chernev’s studies in which an unhealthy side was added to a main One possibility, examined in study 3, is that the apparent discrepancy in findings emerges from a small but important difference between the Chernev studies and our own in terms of additional information presented to participants before completing the task. One of the original studies specified the use of a reference food The use of a reference food in previous Chernev studies that report the negative calorie illusion, and the fact that our first two studies, which did not use a reference point, did not elicit the negative calorie illusion, raises the interesting possibility that the presence of a reference food may have an important role in generating the negative calorie illusion. It is known that calorie estimates are inherently uncertain estimates, and in the absence of any accurate knowledge about the calorie content of food, participants may use the calorie content of the reference food as an anchor and then adjust this to estimate the content of the test food By contrast, Chernev proposes that all foods are categorized according to a good/bad dichotomy of healthy or unhealthy (vices or virtues), with meals combining vices with virtues perceived as more healthy than a vice alone. This overall evaluation of the meal’s healthiness is then used to make the calorie estimates If calorie estimates are driven by reference-dependent anchoring and adjustment, participants will be strongly influenced by attributes on which the reference and test food differ as these will be coded as losses or gains, and use calorie knowledge of these attributes alone to adjust the calorie information from the reference. Calorie estimates are therefore very susceptible to the nature of the material presented prior to making the calorie judgment, i.e. the reference food, for subsequent judgments.Thus a reference-dependent anchoring account is able to explain the differences between the findings from Studies 1 and 2, and those from previously published research Since the reference-dependent anchoring account places so much weight on the content of the reference food, which the Chernev account does not, the two hypotheses are empirically discriminable. One instance when the two hypotheses generate opposing predictions is when the reference food includes a small healthy side  and reference food  as the variables of interest. The main predictions of Chernev’s hypothesis were a main effect of test food side dish, and no interaction between test food and reference food, since it is argued that the negative calorie illusion is a function of the combination present in the test food alone. By contrast the main predictions of the anchoring hypothesis were an interaction between test food and reference food, and no main effect of test food, as it is the contrast between the reference food and the test food that are hypothesized to drive calorie estimates.https://requester.mturk.com/, 430 participants, all residents of the United States of America and over 18 years, were recruited via an online panel , or with a small portion of healthy side (n = 110). The other two groups were shown a main meal with a healthy side as the reference, followed by a test food of a main meal item alone (n = 106) or with a small portion of healthy side (n = 111). The reference food used in this study was a simple hamburger (with carrot batons), and the test food used in this study was a cheeseburger (with celery sticks) .The remaining testing procedure was exactly that same as for Studies 1 and 2, with all the same measures taken in the same manner.Analyses of variance were planned on calorie estimates including a main effect of the healthy side in the test food, a main effect of the healthy side in the reference food, and an interaction between the presence of a side in the test food with the presence of a side in the reference food. As for Study 2, analyses for only natural log transformed calorie estimates will be reported.Participants shown the reference with no side judged the main alone to have on average 6.51 ln calories , while the main meal with a healthy side dish was judged fewer calories with on average 6.46 ln calories . By contrast, participants shown the reference that included a healthy side judged the main alone to have on average 6.40 ln calories  while the main with a healthy side was judged to have more calories with on average 6.46 ln calories . Analysis of the log-transformed calorie estimates revealed no significant effect of the healthy side in the test food on calorie estimates  = 0.042, p = 0.84), a significant effect of healthy side in the reference food on calorie estimates  = 4.63, p = 0.03), and also a significant interaction between a healthy side in the reference and a healthy side in the test food on calorie estimates  = 5.24, p = 0.02) 4. LookiAnalysis of variance of the health rating data reveal no significant effect of the healthy side in the test food on health estimates  = 0.83, p = 0.36), no significant effect of healthy side in the reference food on health estimates  = 0.01, p = 0.94), no significant effect of concern on health estimates  = 2.02, p = 0.16).These data provide support for the reference-dependent anchoring and adjustment account of the negative calorie illusion as it was found that the nature of the reference food significantly interacted with the impact of a healthy side dish on calorie estimates. Using a reference food, or anchor, with no incidental healthy food generated the negative calorie illusion as seen in previous studies In addition to providing some insight into the mechanism behind the negative calorie illusion, these findings suggest that the reason for a failure to find a negative calorie illusion in Studies 1 and 2 is due to the absence of any reference or anchoring information. In the absence of such information, there would be no altered salience to any components of the meal, so it can be presumed that those data represented a cleaner account of the influence of incidental healthy foods on calorie estimates.Studies 1 and 2 did not replicate the negative calorie illusion. In addition, Study 2 sought evidence that calorie estimates were mediated by the perceived healthiness of the food, as proposed by Chernev Study 3 tested an alternative hypothesis for the negative calorie illusion, namely a reference- dependent anchoring and adjustment account The current studies taken as a whole support an alternative explanation for the negative calorie illusion to that proposed by Chernev and thereby specify more precisely the contexts in which the illusion is most likely to occur Instead, the findings from Study 3 suggest that the negative calorie illusion results from the use of a reference-dependent anchoring and adjustment heuristic to make estimates about the test food relative to the reference food, whereby the difference between the reference and the test food is coded as a loss or a gain, and thereby influences calorie estimates. This finding is consistent with existing data on sequential calorie estimates Calorie estimates are a simple measure of participant’s perception of foods; however they almost certainly do not reflect actual factual knowledge about a food’s calorie content. It is not currently known whether calorie estimates are related to the expected satiety for a food, or anticipated tastiness. The data from the current studies fail to show that calorie estimates are derived directly from the healthiness ratings of foods. Other studies have shown that calorie estimates are influenced by the restaurant from which a food is purchased Based on the current data, a negative calorie illusion is unlikely to be driving systematic failures in calorie estimations when incidental “healthy foods”, such as fruit and vegetables, are viewed alongside energy dense nutrition poor foods in advertisements or food labels. Foods would need to be viewed in a pre-determined sequence for systematic errors in real-world instances of calorie estimates. A couple of examples when this might occur are when food items are viewed in a meal with courses  or when foods are seen in a specified order as they are positioned on a food menu or within the pathway around a supermarket from the entrance to the checkout tills. Further experimentation within these two particular contexts would be needed to see if biases are present, and if so, what influence they have on preference and consumption of food.The current study provides an attempt to replicate a published finding, along with additional data that adds to our understanding of how participants generate calorie estimates. Alongside the merits of understanding calorie estimates, this study echoes some of the issues of replications in scientific research in general One key limitation of both these studies, and the original studies which these are replicating A further replication of the current study that would be of considerable interest is in exploring whether calorie estimates accurately reflect the true energy content of the food. Such a study would need more controlled photographic stimuli, including cues that allow participants to more accurately gauge the size of the food portions, such as plates, knives and forks, as well as known calorie content for the food, and as such might be better conducted in person rather than online using images.The current set of studies sought to replicate the negative calorie illusion. The results show first, that the absence of a reference food obliterates the negative calorie illusion (studies 1 and 2) and second, that the presence of a reference food reinstates it and demonstrates that it is not a ‘heathiness averaging effect’ as was originally proposed Calorie estimates are an interesting index of our perceptions of the properties of food. They are easily captured and the current studies, together with existing research on calorie estimates, demonstrate the extent to which they are influenced by the context within which a food is presented. Their variation may be a useful measure of our perception of the food we are eating and a target for intervention to alter the choices we make and reduce energy consumption.Figure S1Supplementary Material showing the images of food shown to participants in each experimental group. A: Food images used in study 1: Participants saw one of image of each main dish. B: Food images used in study 2: participants viewed only one of the food images. C: Food images used in study 3: participants viewed one of reference foods followed by one of the target foods.(PDF)Click here for additional data file.


Variability is inherent to rhythmic physiological patterns. Fluctuations in neural patterns are often regarded as noise. However it has been suggested that neurally generated rhythms result from systems that are not homeostatic but instead are homeodynamic 2]. In t. In t2].in vivo models that incorporate chemosensory and mechanosensory feedback which are likely to be necessary mechanisms of respiratory variability. A fundamental source of respiratory pattern generation is the preBötzinger complex (preBötC) which is part of the ventral respiratory column located in the brainstem. Here we use a computational model of the preBötC to analyze the variability of behavioral patterns at both the population and single-cell levels.Studies have addressed the presence of variability of the neural control of respiration in both the clinical context  as well in vitro respiratory slice . It u. It uin ry slice  that areWe focused on two network areas and their influence on burst pattern variability. The first was the tonic drive to preBötC cells. We varied the quantity of tonic inputs and connection densities. We found that an increase in the connection density to preBötC cells produced a decrease in overall linear and nonlinear variability. This is due to the increase in postsynaptic event correlation that results from the combined common inputs. The second area that was studied was the interconnection density between the preBötC cells themselves. Again an increase in connection density produced a decrease in overall linear and nonlinear variability. However, this effect was not as pronounced as that of the tonic drive.


Resolving the kinetics of agonist binding events separately from the subsequent channel gating processes requires the ability of applying and removing the agonist before channel gating occurs. No reported system has yet achieved pulses shorter than 100 µs, necessary to study nicotinic ACh receptor or AMPA receptor activation.Solution exchange systems deliver short agonist pulses by moving a sharp interface between a control and an experimental solution across a channel preparation. We achieved shorter pulses by means of an exchange system that combines a faster flow velocity, narrower partition between the two streams, and increased velocity and bandwidth of the movement of the interface. The measured response of the entire system was fed back to optimize the voltage signal applied to the piezoelectric actuator overcoming the spurious oscillations arising from the mechanical resonances when a high bandwidth driving function was applied. Optimization was accomplished by analyzing the transfer function of the solution exchange system. When driven by optimized command pulses the enhanced system provided pulses lasting 26 ± 1 µs and exchanging 93 ± 1% of the solution, as measured in the open tip of a patch pipette.Pulses of this duration open the experimental study of the molecular events that occur between the agonist binding and the opening of the channel. The kinetic study of ligand-gated ion channels depends on the ability to rapidly exchange agonist concentration on outside out patches. This ability is of great importance in different fields. In Ligand Gated Ion Channels (LGIC) biophysics the application of very short pulses of the agonist Methods to exchange the solution to which an ion channel is exposed include photo-release and hydraulic techniques In the present state of the art, the generation of agonist pulses achieves durations of 200–400 µs The primary factors that limit the speed of solution exchangers have been discussed by Sachs All experiments were done on a patch clamp setup adapted for ultra fast pulses. High solution flow rates were obtained by means of a pressurized system composed of a small nitrogen cylinder (10 l) as a constant pressure source. To avoid oscillation in the flow rate, pressure regulators were not used. Indeed, as the nitrogen consumption was relatively small (70 ml/h), the pressure was constant during the course of an experiment. A homebuilt pneumatic system was used to drive the syringes containing the solutions. This arrangement was made of two 60 ml syringes  joined back to back via their plungers. Thus, one set was connected to the pressurized nitrogen; the other set was filled with experimental solutions and connected to the application pipette. The first set of syringes worked as pneumatic cylinders pushing the plunger of the second syringes set, thereby avoiding the contact of the pressurized nitrogen with the solutions. This prevented the dissolution of the nitrogen into the exchanged solution which leads to the formation of bubbles at the patch. The syringes delivered the solution through polyethylene tubing  to the application pipette. The latter was mounted on a metal holder glued with epoxy glue  to one extreme of a piezoelectric actuator stack . The piezoelectric stack was epoxy-glued to an acrylic base and supported on a 3D translation stage . A custom made piezo amplifier built around a 50 kHz, 30 A power operational amplifier  was used to drive the piezo stack. A multifunction data acquisition  was used to drive the piezo amplifier as well as for acquisition of the patch clamp amplifier data. The recording pipette headstage was mounted on a motorized 3 dimension manipulator  and connected to a patch amplifier . The frequency response of the patch clamp amplifier was tested with a capacitor circuit element and its transfer function was obtained. A nearly ideal capacitor was built by bringing two conductors close to each other A pressure of 1–1.2 bar was applied to the pistons to generate a flow rate of 15–20 µl/s of solution per line. As the diameter of the application pipettes varied in the 100–120 µm range, the flow rate was adjusted accordingly for the area of the tip of the application pipette to assure that the average velocity of the fluid would be ca. 400 cm/s at the tip of the application pipette. The calculation of the flow velocity was made assuming that, at a distance that is half the radius of the application pipette tip, the flow stream diameter equals that of the application pipette tip.4, 2.5 mM NaOH and washed with a solution of 7.5% H2O2 2.5 mM H2SO4. To reduce the width of septum wall of the theta tubes from 10 to 3 µm the pipette tip, was filled up to 1–2 mm with 10% HF 4 when finished. All experiments were performed using recording pipettes  pulled in the micropipette horizontal puller to a resistance of 10–15 MΩ when filled with an internal solution containing 145 mM CsF, 5 mM NaCl, 1.3 mM MgCl, 10 mM HEPES. As 100%, 30% and 10% external solution we used 150, 45 and 15 mM NaCl respectively; but with the same concentration of HEPES, 10 mM. The pH of all solutions was adjusted to 7.4 with aqueous HCl. The distance between recording and application pipettes was set at half the radius (ca. 25 µm) of the application pipette and the angle between them was set at 105°.The application pipettes were made of a borosilicate theta tubes  pulled on a horizontal micropipette puller ; the tip diameters of the application pipettes were adjusted down to 100–120 µm of outer diameter by carefully hand-grinding the tips with diamond lapping films of 1 µm . After grinding, the pipettes were cleaned 1 h in a solution of 0.1 M KMnOm(t), and the Fourier transform of the voltage command applied to the piezo vc(t):The transfer function of the response of a piezoelectric stack alone has been previously measured to optimize the movement of the piezo t)}(ω) indicates the Fourier transform of the function f(t). The voltage command vd(t) that should generate the desired displacement yd(t) is then:Where F {f algorithm to obtain the discrete Fourier transform and it’s inverse. We also used the Black Box approach to correct the transfer function of the patch clamp amplifier and get a better estimate of the rise and fall times of the pulses.Here FPiezo motion upon a voltage pulsed command was measured by the displacement of a laser beam reflected by a gold mirror attached to one end of the piezo. The angle of incidence of the beam was 45°; the movement of the beam was measured with a quadrant photodiode detector placed 6 cm from the incidence point. The reading of the quadrant photodiode was calibrated after moving the piezo known distances with the motorized manipulator (860 Newport).In order to reduce the rise time of the solution exchanger, we varied the pressure applied to the syringe pistons in such a way that the estimated flow velocity out of the application pipette changed between 100 cm/s and 400 cm/s. We measured the current on the recording pipette as we activated the motorized manipulator (velocity: 0.4 mm/s) to move the recording pipette from one stream to the other. We found that the drop in current that occurs when crossing the interface between the control solution  and the experimental solution  showed the expected shape of a diffusive process  at 100 cm/s. However, after we increase the velocity of the fluid to 400 cm/s, the interface showed a staircase shape. We hypothesize that fluid from the bath is being drawn into the interfacial region between the two flows. To test that possibility we set a higher concentration of external solution in the surrounding bath than in the ports: 30% external solution on one port, 10% external solution on the other, while the bath was constantly replenished with 100% external solution . In thisIt was found that a smaller septum counteracts the effect of increasing the velocity very efficiently. Etching the application pipette with hydrofluoric acid 10% in absolute ethanol allowed reducing the width of the septum from 10 to 3 micrometers. Reducing the width of the septum allowed us to maintain an ideal profile and maintain a fluid velocity of 400 cm/s .The next step was to accurately measure the interface between both streams of solution. In the following experiments we use only two solutions, 100% external at one stream, 10% external at the other stream, to increase the signal to noise ratio, critical at high frequency recordings. For the experiments in Taking advantage of the information present in The movement of the piezo alone after a 50 V, 20 µs pulse was optically measured . The pulBy positioning the pipette near the interface, only the movements of the interface occurring close to the application pipette are detected; the movements occurring far from it are missed. On the other hand, by placing the measuring pipette in the middle of the interface and reducing the amplitude of the pulse, it was possible to make a complete measurement of the movement of the interface. The interface was re-calibrated every 10 pulses by applying a triangle signal. We constantly monitored the position of the interface making a fine correction of the position of piezo by varying the holding potential in 0.5 mV steps. This allowed keeping the position of the interface at the beginning of each pulse between 40 and 60% of the difference in current at both sides of the interface. Only traces where the initial position of the interface laid between 40 and 60% were included in the average see . Figure The solution switching system can be modeled as a linear system: the input is given by the voltage fed to the piezo, x(t), and the output is the movement of the interface. The transfer function of this system has enough information to calculate the command voltage needed for the piezo to generate any desired movement within the bandwidth of the electro-mechanical system.s(ω), and of the piezo alone, gp(ω), and that for the Fourier transform of the movement of the system, Y(ω) are shown in s (ω) show the same frequency dependence to the up to ca. 50 kHz, where the amplitude of X(ω) drops to zero. The apparent peak of gs (ω) and gp(ω) at exactly 50 kHz is an artifact caused by the zero value of X at that frequency. The transfer function of the piezo alone showed multiple resonances , that where different from the resonances of the whole system .The amplitude of the transfer function of the system, gThe optimized command voltage to the piezo was a complex signal that started 10 ms before the time of the intended pulse  peaked cWith the aim of optimize further the movement and obtaining a cleaner solution exchange we calculated again the Fourier transform of the movement of the interface, Y(ω), and the corresponding transfer function G(ω) . Y(ω) waBy this procedure it was also possible to produce square pulses of 100 µs. After applying the second round of optimized voltage command of 10V amplitude, a 97 ± 3 µs pulse, with 10 µs rise time and 12 µs decay time was obtained . It exchThe general aim of this study was to find an experimental strategy for producing the short exchange pulses required to separate binding from gating in fast LGIC The flow velocity in our experiments is 40 times bigger than that used in commercial or state of the art devices. Because our system isolates the pressurized gas from the solutions being injected it avoids the formation of bubbles that might collide and break the patch. We also carefully removed air bubbles and filtered solutions of contaminating particles. With this system we obtained flow rates between 100 and 400 cm/s. Higher velocities may be possible but may compromise the stability of the measurement We did not measure the actual flow rate of the solution reaching the measuring tip. For streamline flow in a cylindrical tube, a paraboloidal velocity profile would be expected; the situation here is more complex since two flowing streams are separated by a thin septum and the plume is ejected into the surrounding bath. We therefore presented an estimate based on the volume flow rate and the perfusion tip dimensions.A high velocity step of the moving perfusion tip might influence the effective width of the interface in the case that the translational velocity is higher than the perfusion velocity. It can even disrupt the interface in the case of a Reynolds number in the turbulent regime (>4000). This was not the case in present experiments. We estimated that the translation velocity of the perfusion tip was at most 16 cm/s for a 10V step. This velocity is 25 times slower than the estimated fluid velocity. Furthermore, even at the high velocities used in this work, the Reynolds number is 400, corresponding to a laminar regime (<2300). Therefore, we do not expect much effect of the piezo translation on the interface width.High flow rate would have an effect on the membrane tension that would activate mechanosensitive channels. This effect would show up as an increased leakage current. As it is likely that the flow rate would change at different distances from the interface, it is important to perform control experiments with external solution at both streams. Those control experiments would detect if there is an effect of the flow rate gradient over mechanosensitive channels. Furthermore, experiments at different flow rates are necessary to address the possibility of a modulation of the ligand gated receptor by membrane tension.We found that the width of the interface increases with the width of the partition between the two steams. This effect was more pronounced at high flow velocities because the solution from the bulk is being dragged into the interface especially when the septum is relatively thick. This causes the interface between the streams to become contaminated with solution from the bulk. This fact was made evident by using streams with lower concentrations than that in the bulk solution. Fortunately, this contamination could be alleviated by diminishing the thickness of the septum.The velocity of the interface movement in our experiments reached 15 cm/s, 4 times faster than the state of the art (3). We also increased the bandwidth to 100 kHz. We used a small excursion high frequency piezo and we drive it with a custom made, 100 kHz, 30 A piezo amplifier. We measured the transfer function of this whole system and after applying simple algebra (Eq. 2) we obtained the time course of the voltage signal to the piezo actuator that produces a pulsed movement of the solution interface.The combination of the enhancements discussed above made it possible to generate a huge reduction in the duration of the pulse: 25 µs pulses with rise and fall times of 8 µs. In comparison previous arrangements which produced 200 µs pulses with 80 µs rise and fall times using the black box approach on a 10 kHz piezo actuator, with 6 cm/s flow velocity and with a septum 10 µm thick.The response of the piezo alone shared some characteristics with the response of the whole solution switching system: both lasted about 10 ms and the initial oscillations have a period of 18 µs. However, it is clearly insufficient to predict the response of the whole system. Perfusion, wobbling of the interface and vibrations of the application pipette introduce substantial complexity to the transfer function, stressing the adequacy of measuring directly the movement of the interface in order to optimize its movement. An alternative method to get sub-millisecond pulses An option to the use of piezoelectric actuators on parallel streams consists of using solenoid valves as the switching mechanism: the valve turns off one of a pair of colliding streams. In this way 1.0 ms pulses with a rise time of 25 µs Our results were obtained on an interface of only 0.36 µm width. Considering that the transverse motion of the stream is 16 cm/s, the moving interface should cross the position of the pipette in just 2 µs. The observed rise time of 8 µs needed for the concentration to change from 10 to 90% was four times slower. Although this value was obtained after correcting for the measured frequency response of the patch clamp amplifier, it might still be limited by the bandwidth of the patch clamp amplifier. In a similar way, previous results on an interface width of 700 nm showed a rise time of 80 µs when the moving interface was calculated to cross in only 14 µs. Aside from the limited bandwidth of the measurements, these discrepancies may arise from diffusion through the unstirred layer that sits against the patch pipette tip. Sachs examined these phenomena using finite element models The very short pulses here reported would be a powerful tool for the experimental study of the molecular events that occur between the binding of the agonist and the opening of the channel. Pulses lasting 200 microseconds on rat-P2X2 receptors showed a time delay between the application of the agonist and the opening of the channel In addition, these pulses should be useful to mimic the chemical synapse in the nervous system


ARCIMBOLDO combines the location of small fragments with Phaser and density modification with SHELXE of all possible Phaser solutions. Its uses are explained and illustrated through practical test cases. ARCIMBOLDO, based on the combination of locating small model fragments such as polyalanine α-helices with density modification with the program SHELXE in a multisolution frame, has evolved to incorporate other sources of stereochemical or experimental information. Fragments that are more sophisticated than the ubiquitous main-chain α-helix can be proposed by modelling side chains onto the main chain or extracted from low-homology models, as locally their structure may be similar enough to the unknown one even if the conventional molecular-replacement approach has been unsuccessful. In such cases, the program may test a set of alternative models in parallel against a specified figure of merit and proceed with the selected one(s). Experimental information can be incorporated in three ways: searching within ARCIMBOLDO for an anomalous fragment against anomalous differences or MAD data or finding model fragments when an anomalous substructure has been determined with another program such as SHELXD or is subsequently located in the anomalous Fourier map calculated from the partial fragment phases. Both sources of information may be combined in the expansion process. In all these cases the key is to control the workflow to maximize the chances of success whilst avoiding the creation of an intractable number of parallel processes. A GUI has been implemented to aid the setup of suitable strategies within the various typical scenarios. In the present work, the practical application of ARCIMBOLDO within each of these scenarios is described through the distributed test cases.Since its release in September 2009, the structure-solution program  Analogously, the method tests many hypotheses assembled from secondary-structure fragments and, while most of them remain a ‘still life’, density modification is effective in revealing and identifying the true portrait of the protein being solved.ab initio case, ARCIMBOLDO has been expanded to other scenarios that enable it to tackle larger structures with poorer data, and its user friendliness has been improved through the incorporation of a GUI to help the user set up and parameterize an ARCIMBOLDO run. The same frame as that used for the ab initio case allows the exploitation of other sources of previous stereochemical knowledge, such as low-homology models or experimental phases from derivatives that are too noisy to be interpretable on their own. The present work describes the use of ARCIMBOLDO in its different modes and discusses its application to various test data sets.Since its first use for the 2.ARCIMBOLDO is very demanding in terms of computational power. Thus, it is coupled to the use of a grid running Condor  or at poorer resolution (2.1 Å). Often 2.5 Å resolution data is sufficient for successful fragment location, but as the resolution becomes worse expansion from the partial structure through density modification and autotracing does not succeed. In such cases, a more complete starting hypothesis or additional information will be needed in order to reach a successful solution and prevent the density-modification expansion from becoming stuck.The conditions, use scenarios and flow control, together with the necessary files and parameters to be set within Structures have been solved in any crystal system or with noncrystallographic symmetry as high as sevenfold; thus, symmetry does not pose an intrinsic limit. The possible size limit on the structures to be tackled by these methods is strongly related to the computational power available: larger structures require the location of more fragments and more trials. Success may be reached by increasing the CPU power. Intrinsic barriers have so far not been determined but cannot be excluded.3.1.ab initio successes have been obtained exploiting their presence.The simplest case is when all the available previous information is reduced to a set of native data and the amino-acid sequence. From this, secondary-structure prediction algorithms can derive the number and length of expected α-helices and β-strands. α-Helices tend to be very constant in their main-chain geometry, especially over a short range (10–14) of amino acids. In contrast, the higher variability and shorter span of β-strands make them less useful as search fragments and so far no ARCIMBOLDO and the order and number of copies to be located for each of them has to be specified. When searching for helices of different length, it is convenient to start with the larger ones, as short helices could also be accommodated in the sites of the longer ones and packing filters would prevent further progress.Different fragments can be input to ab initio are small but very accurate , a smaller mesh should be selected rather than the default Phaser grid. Empirical values found to be suitable are 1.0–3.0° for the rotation search and 0.3–0.6 Å for the translation search.As the fragments used for ab initio phasing, we will consider the structure of PRD2 in space group P21  against the final structure better than 87°. For the third fragment, one of the top ten solutions showed an MPE of 57°. Having found a solution within this subset, the remaining ones were not expanded. In this case, expansion of all 153 solutions consisting of three fragments would phase the structure in two more cases. Fig. 2a) displays the three sets of fragments. The helices in red and orange are common to all three winning solutions and the blue ones are different in each case, although the two on the left overlap over a large span  and the one on the right is rather incorrectly placed . The final map, shown in cyan, reveals that their positions are otherwise extremely accurate.The run is set up by cutting the resolution for the fragment search at 2.5 Å, the rotation step at 1.5° and the translation step at 0.7 Å. After every step solutions are limited, if necessary, to keep their number within tractable limits. Furthermore, after each step fragment expansion is attempted on the ten solutions with the highest 3.2.et al., 2009et al., 2011ARCIMBOLDO flow in three different ways.Combination of molecular replacement and weak anomalous data has proved to be useful for automatic structure solution  structure in space group SHELXE uses the anomalous substructure and the file containing the anomalous differences and phase shifts to phase the native data, in combination with fragments, if present. In this case, 30 cycles of density modification and three cycles of autotracing already bootstraps with one six-S-atom substructure. If the second anomalous fragment is searched for, the correct solution is even clearer from the figures of merit (LLG = 180 versus 119 and TFZ = 8.6 versus 5.2 for the next best). Fig. 2b) shows the density map and main-chain trace obtained as well as the sulfur substructure.Search and optimization with this anomalous fragment was performed cutting the anomalous data to a resolution of 2 Å. The first fragment produces 20 translation solutions, of which five are unique and have similar figures of merit. At the expansion stage, ARCIMBOLDO and combined with the search for model fragments. In this case, it is possible to restrict the search for model fragments and perform brute-force rotation and/or translation searches, as a secondary-structure element linked to an anomalous fragment might be predictable, such as the two helices linked through a disulfide bridge in the VTA fold or in fact any case where a cysteine would be contained in a region predicted to be α-helical. A key point is that substructure and fragments have to refer to the same origin if their phasing information is to be combined. In many space groups refinement allows partial solutions to drift away from the starting position in one or more directions. ARCIMBOLDO can be restarted from any point in its flow. This allows the input of any kind of previous information, be it a partial solution made up of fragments, an anomalous substructure or a combination of both. When searching for further fragments, the anomalous fragment must be input as part of the native solution.The second possibility is the combination of experimental phases and fragments. In most cases where anomalous or MAD data are available, the substructure can be determined more effectively by dual-space recycling methods. If the experimental phases derived from the substructure are not accurate enough to provide an interpretable structure solution, they can be input into A third alternative is deriving an anomalous map to search for the substructure from the phases provided by a partial model. In this case the structure is probably good enough for autotracing to bootstrap, but recycling the search for the substructure is much faster than autotracing, and combining both sources of information probably renders a better final map.3.3.ARCIMBOLDO provides a means of testing a list of alternative fragments in parallel and specifying a figure of merit (LLG or Z score) to let the procedure select the optimal one. This list may be a file explicitly input into the script or passed as an external file containing one PDB or one gzipped tar file of multiple PDB files in each line.Exploiting any particular stereochemical knowledge that may be available is possible. For instance, side chains may be modelled on a predicted helix and various combinations of the most frequent conformers may be set up. Even if no homologous structure leads to a successful molecular-replacement solution, poor homology models will provide a reasonable hypothesis about the general fold, as would particular local knowledge of an active site. In such cases, rather than building up the fold from sequentially added model fragments, it is possible to dismember the model into pieces and input them as search fragments. Usually, such information opens up several possibilities that have to be tested and, ideally, confirmed or discarded early on. ab initio case, PRD2 in space group P21 (PDB entry 3gwh), is used here. Four alternative fragments are proposed: a model polyalanine helix with 14 residues; a helix with side chains in the most represented conformers from Leu74 to Gln87 modelled with SCWRL4 . Comparing the results of this approach with that starting from main-chain helices, the main difference is that the structure is solved twice after two fragments, rather than requiring the placement of three helices to obtain the first solutions. Two of the ten two-fragment solutions expanded through density modification led to recognizable solutions, with traces of 103 and 79 amino acids characterized by CCs of 26.5 and 16.1%, respectively. Their MPEs compared with the final structure were 58 and 72°, respectively. Figs. 3a) and 3b) display the overall structure with the located fragments superimposed and the final map and detail of the fragment placed on the final structure. As searching for successive fragments is much more time-consuming than performing many single-fragment rotations, it may be more effective to invest time initially to screen through fragments with side chains in all possible standard conformer combinations that will not clash than to have to place more fragments. Unfortunately, solving fragments may not always be unequivocally identified through such early-stage figures of merit but, in any case, it may be useful to prioritize the trials to be run.The same example as provided for the P43212 the asymmetric unit contains two copies of the molecule, totalling 88 amino acids. Each molecule contains two α-helices: one of nine and another of 13 amino acids. In these cases, it is convenient to search first for two copies of the larger helix of 13 residues and then for two copies of the shorter one. From the secondary-structure prediction, the position within the helix where a cysteine is located is predetermined. Cysteines within a helix possess only two favourable conformers. Thus, this information can be exploited in the fragment. Indeed, searching for polyalanine helices gives many more solutions to the rotation function under the same conditions (94 versus eight) and the whole process is accelerated by searching for a helix with a cysteine side chain. What is remarkable in this case is that even solutions where the cysteine has been misplaced may lead to phasing the structure, as can be seen in Fig. 3c) and 3d) show the final phased map, with data extrapolated to a resolution of 1.0 Å  is demanding but doable, 33 000 become utterly intractable for the file system. Even if it were possible to organize the run in such a way that they are all calculated, it is more efficient to discard trials eventually leading to failure as soon as possible and to spot those solutions that are more likely to succeed and design an express way to push them forward in the process and save time by stopping computations if they lead, as expected, to success.The Condor grid is used to allow the calculation of a large number of processes in parallel. As figures of merit cannot reliably characterize the successful solutions at their early stages, it is important to push a very large number of hypotheses to make structure solution possible. Still, it is obvious that any system will have a limit and exponentially increasing the number of jobs from fragment to fragment would swiftly lead to a collapse in the procedure. The structures provided as tutorials and used to illustrate the examples in this paper are comparatively small, but the case of eIF5 (PDB entry (i) Select one among the choice of fragments in PDB format according to an FOM.Phaser, cutting the resolution to typically 2.1–2.5 Å.(ii) Perform fast rotation function with Phaser using the resolution cutoff to leave out poor data.(iii) Perform fast translation function with Phaser.(iv) Perform packing filtering with Phaser to sort solutions and discard the bottom 20% of each packet.(v) Perform LLG rescoring with Phaser to improve and cluster out equivalent solutions and discard the bottom 20% of each packet.(vi) Perform refinement and phasing with Z score, number of solutions…).(vii) Sort solutions according to an FOM of choice  Expand the top solutions through density modification and autotracing with This process is iterated over the number of fragments specified in the search parameters. All surviving solutions of n parameters are used to start possible n + 1 fragment structures.The general flow of the procedure is as follows.The parameters that have been introduced to this end are a limit on the number of rotations to be launched, $rot_limit, and a secondary limit on the rotations, $rot_sec_limit. The first number will allow as many solutions to be taken from the resulting solution files of the last rigid-body refinement. Once this number has been filled, the second limit is used to take as many solutions from each further rigid-body packet file. The reason for this choice is that solutions are not truly independent. Within the same file, solutions tend to share some parentage. If the top figures of merit are apparent from the start, forcing a sort from the beginning would help. Otherwise, it will just make sampling more uniform. Thus, even if FOMs are lower, it is good to retain part of the various packages generated.versus solutions containing few peaks. This limit is relative; thus, an average of the number of solutions is estimated as from the second fragment and from that point on translation solutions exceeding this limit are completely discarded. This limit is expected to decrease from fragment to fragment. It does so in the above-illustrated case of 2iu1, but general statistics cannot be provided as they would require too much CPU time.For the translations some optional limits can also be switched on. Solutions containing a lot of peaks within 75% of the top peak can sometimes be discarded ARCIMBOLDO run and avoid spending any more time on an already solved structure. To this end, an ‘express lane’ has been implemented to allow more likely to succeed partial solutions to be given priority in order to save time.In addition, identifying solutions early on may be exploited to stop the whole 3.5.ARCIMBOLDO is tedious and error-prone. Therefore, a GUI has been programmed in C# and is distributed with the release. It allows the input of templates for different scenarios for the modification of parameters to suit the case in question. Environmental variables or paths to the executable may be changed to suit the computer system. It checks and analyzes the input files as well as the choice of parameters and will give warnings whenever any parameter or combination appears to be inappropriate. This is still not unavoidable as it may be run remotely from the site where ARCIMBOLDO will be run; for instance, if a run should be performed outside a graphical environment, such as a supercomputer. However, the user is allowed to override all limits. Fig. 4Inputting the right choice of parameters into 4.SHELXE can be accomplished on a Condor computer grid to phase difficult macromolecular structures within the frame of ARCIMBOLDO.Brute-force multisolution combination of model fragments or alternative models consistent with previous stereochemical information, anomalous fragments or substructures and density modification and autotracing within the program


Observers made a saccade between two fixation markers while a probe was flashed sequentially at two locations on a side screen. The first probe was presented in the far periphery just within the observer's visual field. This target was extinguished and the observers made a large saccade away from the probe, which would have left it far outside the visual field if it had still been present. The second probe was then presented, displaced from the first in the same direction as the eye movement and by about the same distance as the saccade step. Because both eyes and probes shifted by similar amounts, there was little or no shift between the first and second probe positions on the retina. Nevertheless, subjects reported seeing motion corresponding to the spatial displacement not the retinal displacement. When the second probe was presented, the effective location of the first probe lay outside the visual field demonstrating that apparent motion can be seen from a location outside the visual field to a second location inside the visual field. Recent physiological results suggest that target locations are “remapped” on retinotopic representations to correct for the effects of eye movements. Our results suggest that the representations on which this remapping occurs include locations that fall beyond the limits of the retina. With our head and eyes steady, our normal binocular vision covers a visual field of about 200 to 220 degrees of visual angle In this paper, we ask what happens to the representation of a target when remapping specifies a location outside the visual field, as would happen for any target near the edge of our visual field when we make a saccade away from that target. Will the target still have an active representation despite the extra-retinal location? We can easily imagine that we maintain target representations in memory for objects we have seen but that are no longer in view We adapt a simple apparent motion task that we developed to assess the accuracy of the compensation (remapping) for saccades In our study here, we simply move the first dot to the edge of the visual field and follow it by a saccade away from its location. In order to update that location on a retinotopic representation, it must be remapped outside the visual field, because, if it were still present after the saccade, its location in space would now fall beyond the limit of the retina.visual cells that represent extra-retinal space.We reported here that observers do see apparent motion across a saccade even though its first location falls outside the visual field by the time the second position is presented. Since the first and second presentations are chosen to fall at approximately the same retinal location (probe displacement is matched to saccade amplitude), the perception of motion suggests that apparent motion is computed in spatial not retinal coordinates. This result has also been reported in several previous articles Ten volunteers from Université Paris Descartes took part in the experiment . All had normal or corrected-to normal vision and gave informed consent. The experiment was carried out according to ethical standards specified in the Declaration of Helsinki and was approved by the Ethics Committee from the Université Paris Descartes. All observers gave written informed consent before participating in the experiment.2) and red dots (30.0 cd/m2) on a gray background (100 cd/m2) presented on a gamma-linearized Apple iMac built-in 24″ TFT display  set 60 cm in front of observers’ eyes (see “front screen” in 2) on a gray background (100 cd/m2) presented on a gamma-linearized Apple 24″ LED-backlit TFT display  placed in observers’ left visual periphery  or if head position changed of ±2.5 cm in any direction from an initial head calibration angles and locations.Observers were seated in a quiet, dimly lit room. Fixation markers were 1°-diameter green (30.0 cd/m2) or light gray (175 cd/m2) on a mid-gray background (100 cd/m2). The probe was positioned 2° to the left of the side screen center and based on observers’ discrimination, we moved the screen in order to increase or decrease the probe eccentricity. We stopped this procedure when observers said that they could not see anything on the side screen and when they were close to chance level on 20 consecutive trials (50% ± 5% correct). This adjustment procedure assured that observers were unable to see the left half of the side screen when they correctly fixated the right marker on the front screen . This initial sequence helped observers to synchronize their saccades with the exchange of the two dots and to prepare themselves for the main cycle. In the main cycle, two apparent motion probes were presented sequentially on the side screen, one before and one after the saccade. Each probe was presented during 400 ms, with the first turned off 150 ms before the exchange of the green and red markers while the second turned on 150 ms later, giving then 300 ms for observers to complete their saccades. Probes were presented on the horizontal midline of the side screen and separated by the same offset as that between the fixation and saccade markers on that trial . Finally, the order of appearance of these probes was equiprobably right-first or left-first, producing equal numbers of leftward and rightward motion trials. At the end of the main sequence, a red ring appeared around the green fixation marker indicating that the observers should report whether they saw or not any motion on the side screen.Because the side screen was positioned in such a way that its left half could not be seen when the observers fixated at the right fixation marker of the front screen, the combination of the two saccade directions and the two motion directions give the four experimental conditions described in http://cavlab.net/ExtraretinalMovies). The spatial location of the first probe should therefore be remapped outside of observer’s visual field, if it can be. We called that condition, “extra-retinal remapping”. Note in this case, that on the retina, both the first and second probe fall at approximately the same location at the edge of observer’s visual field, one before and one after the saccade. The remapping is required to compute the retinal location where the first probe would have fallen after the saccade if it were still there, in order to detect any changes in its position that occurred at the same time as the saccade.In the first condition , both thhttp://cavlab.net/ExtraretinalMovies). Again to predict the spatial position of the first motion probe following the saccade, its position is remapped by the amplitude of the saccade but in the opposite direction. In this case the remapped location of the first probe now falls inside the observer’s visual field. We therefore called this condition “intra-retinal remapping”.In the second condition , observend probe not visible2” condition, the saccade goes rightward while probes moved leftward on the side screen . In this case, although the first probe location may have been remapped, the second probe falls outside observer’s visual field, and thus no motion should be perceived after the saccade, testing whether we had properly positioned the side screen and thus the position of the probes. Finally, in the fourth condition . In this case, the first motion probe appeared outside of the observer’s visual field and thus no motion should be perceived after the saccade (again testing whether we had properly positioned the side screen).In the third condition , called ondition , called We evaluated the proportion of motion reports for the 4 experimental conditions (described above) for all saccade amplitudes tested. When inaccurate saccade trials or trials where head movement exceeded our criteria from the initial head calibration position were detected on line, they were rejected and replaced . We then re-analyzed the eye-tracking data offline in order to select only trials where the motion probes were presented trans-saccadically. We thus looked for trials in which the saccade started after the first probe offset and ended before the second probe onset. Within addition we also rejected trials with blinks and those that failed a finer offline evaluation of saccade accuracy. This correction led us to reject a further 548 trials, leaving 77.2% of selected trials . Note that maintaining a steady head position was not a major source of trial rejections as 84.7% of the rejections were due to saccades occurring too early . The screening left an average of 185±16 trials per observer, ranging from 45.4% (GL: 109/240) to 97.9% (JT: 235/240).p<0.001) and no effect of the saccade amplitude  = 0.67, p = 0.52). There is no significant interaction between these variables  = 0.92, p = 0.49). We therefore collapsed our data across the different saccade amplitudes (p = 0.55). These results are significantly different from the control conditions  = 47.11, p<0.001), where motion was reported in about 1 or 2 trials out of 10, 15.0% ± 4.6% for the “2nd probe not visible” condition and 12.0% ± 4.8% for the “1st probe not visible” condition  = 1.22, p = 0.30). In these two control conditions, one or the other of the two probes should not have been visible so we would expect no report of motion. These reports may arise from response errors and guessing but are most likely a consequence of the very liberal criterion we gave to observers. They were instructed to report any kind of motion they saw in the far periphery on the side screen. Post-experimental debriefing revealed that some observers reported both seeing motion and seeing one probe on some trials. They explained that they considered a small jitter of the single probe seen in far periphery as being motion to report. Nevertheless, some of these motion reports in the control conditions could reflect errors in our calibration of the visual field limit. This would suggest that for at most 15% of the trials, the more peripheral stimulus still fell within the visual field. Even this maximum possible level of miscalibration cannot account for the motion reports on 77% of the extra-retinal remapping trials when the location of the first probe, originally within the visual field, is supposed to fall outside the visual field following the eye movement.plitudes . In bothp<0.05, one-tail t-tests). However, 2 observers, CM and NB, showed a different pattern of results. CM showed similar frequencies of motion reports in the conditions with two visible dots vs one (t(1) = 1.71, p = 0.16). At the end of the experiment, CM explained that she experienced motion even when she saw only a single dot. In that case she perceived motion as briefer and of shorter amplitude than when she saw two dots, but reported it as motion nonetheless. On the other hand, NB rarely reported seeing motion in any condition (t(1) = 3.27, p = 0.05). At the end of the experiment, we asked her to report if she saw apparent motion when the probes were displaced while she maintained fixation at the left marker (so that both probes were visible and moved without any intervening saccade). Interestingly, she didn’t report seeing motion suggesting that the distance between probes might have been too large or the delay between the two probes to long for her to see motion.Next, we determined whether the pattern seen across observers also held in individual results. p = 0.40). Critically, in both the extra and intra-retinal remapping conditions, when the probes’ retinal offset was around 0°  when the first probe location still fell within the visual field after the saccade.Apparent motion was reported in these conditions even though the size of the saccades and the displacement of the probes were matched to produce, ideally, no displacement on the retina. In fact, of course, saccade may under- or overshoot but when we analyzed the frequency of motion reports, it was constant, independent of the actual small offset on the retina (from −2° to +1°) caused by inaccurate saccade landings, including the small range around no displacement. This result replicates the finding of Rock & Ebenholtz In the remaining two conditions, either the first or second probe fell outside the visual field when it was presented and should have been invisible. The frequency of motion reports here was much lower (12 to 15%) indicating that our original calibration to locate the edge of the visual field was accurate.Our results show that objects that move in the world are seen to move even if there is no displacement on the retina Alternate proposals for saccadic correction when applied to our probes in the far periphery would also lead to a requirement for extra-retinal representation. For example, with “reference object theory,” a memory of the saccade target landscape is used to locate the original saccade goal so that no efference copy is needed to predict its location In our procedure, we used apparent motion, a type of visual motion that for large displacements cannot be explained by simple motion receptors The perceptual effect we report differs from the more general ability to remember the location of an object previously seen but no longer visible. In our case the perception of motion suggests that basic visual representations of location underlie the effect rather than memory of location. Even without intervening saccades and possible extra-retinal locations, apparent motion is not seen for probe-to-probe intervals beyond about 400 ms Our results suggest that positions outside the visual field are coded in saccade and attention maps, however, we cannot determine in this experiment whether the effective extra-retinal location actually corresponds to the spatial location of the first probe. Alternatively, all remapping or predicted locations that would lie beyond the edge of the visual field may simply be referred to the edge of the visual field. In this case, our stimuli would give an impression of a motion path half as long as the actual path. In a follow up experiment, we plan to ask observers to report the length of the motion path, and point to the first dot location to determine if there is any compression of locations at the edge of the visual field. Alternatively, we could add a vertical displacement to one of the two probes and ask observers to report the direction of the motion from which we could geometrically extract the length (as suggested by our reviewer).We show here that the perception of motion is reported between two probes when a saccade intervened between the presentation of the first and second probe, even though, in some conditions, when the second probe was presented, the effective location of the first probe lay outside the visual field. This result suggests that apparent motion can be seen from a location outside the visual field to a second location inside the visual field. The probe locations were arranged so that the shift between two distinct positions in space caused them to fall at approximately same position on the retina. The fact that apparent motion was seen under these conditions indicates that the motion is seen in spatial not retinal coordinates Our interpretation rests on the subjective motion reports of our observers. In both conditions where the first and second probes are presented within the visual field, observers report motion on about 75% of the trials and this figure is unaffected by whether the first probe’s location lies outside the visual field after the eye movement. So we believe that observers are reporting the phenomenal experience of motion, as requested, and not just reporting the displacement of the perceived (and remembered) locations. Displacement reports (not based on motion) would have reached 100% in these conditions with both probes visible. We do not believe that the eye movement itself is triggering a percept of motion as the great majority of cases with one of the two probes not visible led to reports of no motion.Nevertheless, it is clear that this is only a first evaluation of extra-retinal motion percepts and that further studies that go beyond these subject motion reports are needed. If our first results here hold up, it suggests that areas representing visual stimuli in retinotopic coordinates have cells that respond to extra-retinal space, beyond the margins of the visual field. These cells keep track of targets that have just moved outside the visual field. If these stimuli then move to return to our field of view, we see them not as simply reappearing but as moving.