When faced with intertemporal choices, people typically devalue rewards available in the future compared to rewards more immediately available, a phenomenon known as temporal discounting. Decisions involving intertemporal choices arise daily, with critical impact on health and financial wellbeing. Although many such decisions are “experiential” in that they involve delays and rewards that are experienced in real-time and can inform subsequent choices, most studies have focused on intertemporal choices with hypothetical outcomes . The present study focused on experiential intertemporal choices. First, a novel intertemporal choice task was developed and validated, using delays experienced in real time and artistic photographs as consumable perceptual rewards. Second, performance on the experiential task was compared to performance on a classic intertemporal choice task with hypothetical outcomes. Involvement of distinct processes across tasks was probed by examining differential relations to state and trait anxiety. A two-parameter logistic function framework was proposed to fit indifference point data. This approach accounts for individual variability not only in the delay at which an individual switches from choosing the delayed to more immediate option, but also in the slope of that switch. Fit results indicated that the experiential task elicited temporal discounting, with effective trade-off between delay and perceptual reward. Comparison with the hypothetical intertemporal choice task suggested distinct mechanisms: first, temporal discounting across the two tasks was not correlated; and second, state and trait anxiety both were associated with choice behavior in the experiential task, albeit in distinct ways, whereas neither was significantly associated with choice behavior in the hypothetical task. The engagement of different processes in the experiential compared to hypothetical task may align with neural evidence for the recruitment of the hippocampus in animal but not in classic human intertemporal choice studies. Temporal discounting, or delay discounting, refers to the natural tendency to de-value rewards available in the future compared to rewards available more immediately in the context of intertemporal choice tasks –3. DecisIn light of the ubiquitous nature of intertemporal decisions, there has been much interest in identifying their cognitive and neural mechanisms. Animal models generally agree with brain imaging studies on the recruitment of a valuation network involving the ventral striatum and ventromedial prefrontal cortex –16. Striexperience the delays and consumption of rewards in real-time after they make their decisions . Reward values can therefore be revisited based on the experience of delays and rewards during the task. By contrast, most human research on the cognitive mechanisms underlying intertemporal choice has been conducted using questionnaire-type tasks, consisting of a series of hypothetical choices between a smaller reward available sooner and a greater reward available after various delays  [One key difference between human and animal tasks is that animals must  year?”) . In such year?”) .The premise that different cognitive processes may be recruited depending on the experiential versus hypothetical nature of the task remains to be demonstrated in humans. Indeed, it is commonly assumed that temporal discounting across a variety of tasks in humans is supported by a common underlying mechanism , as evidThe present study aims to compare experiential and hypothetical intertemporal choice in humans by examining performance in a decision task with real-time delays and consumable rewards and in a classic task with hypothetical delays and rewards. We elicit temporal discounting in both cases using a simple binary decision format, involving a smaller reward delivered now and a fixed larger reward delivered after various delays . There is widespread recognition that temporal discounting can be modeled by a hyperbolic tradeoff pattern between delay and reward in hypothetical intertemporal choice tasks , 61. Somk are typically converted to log k for statistical analyses, indifference points are generally plotted using linear time scales. Such practice has obscured the underlying presence of an S-shape in the indifference curve, and has rendered the interpretation of log k less intuitive. With a logarithmic timescale, −log k can be interpreted as the log-delay at which the participant switches between consistently choosing the delayed option and consistently choosing the more immediate option  vary has been suggested to account for individual variability in the subjective perception of time [In addition to making the logarithmic timescale more explicit, the logistic framework also allows for a flexible slope at the inflection point by incorporating an additional parameter, ic model , 67. In  of time , akin to of time .  and mean education of 12.8 years (SD = 1.1), who indicated from self-report that they were free from major psychiatric disorder or neurological illness including attention deficit/hyperactive disorder (ADHD). This sample size was similar to previous studies that compared within-participant behavior across intertemporal choice tasks [M = 13.6; SD = 7.9), as measured by the Center for Epidemiologic Studies Depression Scale, Revised [N = 243, M = 16.4, SD = 13.5, t(43) = -1.9, p = 0.060, Cohen’s d = 0.25) [Participants were 44 female college students with a mean age of 19.0 years  . The Welwww.pexels.com) to include only pleasant content , with 85% of the photographs featuring primarily nature scenes. Because novelty was assumed to constitute a large part of the rewarding experience, photographs were drawn randomly from the bank of preselected photographs without repetition. Examination of photograph distribution across participants showed that they indeed viewed 85% of nature photographs on average , reflecting adequate functioning of the randomization algorithm and homogeneity in photograph content across participants.Capitalizing on the rewarding effect of novel perceptual information , 60, we During the task, participants had to decide between viewing a partially occluded photograph immediately or a non-occluded photograph after a delay. Immediate options comprised 10 possible occlusion levels and were constructed using varying line thickness and spacing that revealed 13%, 28%, 45%, 60%, 70%, 80%, 88%, 95%, 97% and 100% of the full photograph. Delayed options comprised delays of 1, 2, 4, 6, 8, 10, 12, 14, 16, 20, and 25 seconds.For each participant, a series of choices was created using a semi-adaptive dichotomy algorithm, allowing efficient determination of indifference points at each preselected delay. Indifference points refer to the occlusion level for which viewing an occluded photograph now and viewing the full photograph after that delay have equivalent subjective value. For each preselected delay, the algorithm kept track of the uncertainty range for the indifference point. The uncertainty always ranged between 1 and 10 at the start of the task, corresponding to the ten available occlusion levels. On subsequent trials, the occlusion level of the immediate option was selected by each time cutting in half the uncertainty interval. For example, for decisions involving a delay of 10 seconds, the first trial involved viewing a photograph with occlusion level 5 now or a full view of that photograph after a 10 second delay. If the participant chose to wait, the uncertainty interval for a 10 second delay was reduced to between 1 and 5, and the next trial involved choosing between viewing a photograph with occlusion level 3 now or in full view after a 10 second delay. On each of the subsequent trials with a 10 sec delay, the uncertainty interval was again halved until it converged to zero, generally after 3 to 4 trials. In order to promote engagement with varied decisions, the occlusion level of the first trial, rather than starting systematically at level 5, was randomly chosen among levels 4, 5, and 6. Trials with different delays were interspersed, with random selection of delays for each trial among those that had not yet converged to an indifference point. The semi-adaptive algorithm was run twice yielding two indifference points per delay, for a total of 70 to 80 test trials per participant depending on the speed of convergence of the algorithm.On each trial, choices were represented visually on the screen by means of two rectangles filled with a static pattern. The rectangle corresponding to the immediate option was occluded by black lines with orientation, thickness, and spacing identical to the lines that would occlude the photograph at the time of reward see . The recParticipants were given detailed instructions at the beginning of the task and a chance to practice. They were told that the study examined how people make choices about viewing pictures and how seeing a partial view of a picture may affect those choices. To highlight the quality of the pictures and promote interest, participants were told that the photographs were taken by amateur photographers for a contest, and that their task was to indicate on each trial their choice between seeing a partial view of a photograph right away or a full view of the photograph after some delay. Participants initially became acquainted with viewing occluded photographs through presentation of two successive screens, each featuring the same picture with three different occlusion levels. They were then guided through two example trials with the examiner demonstrating use of the response buttons. The same trial was presented twice so that the examiner could demonstrate the effect of choosing the occluded photograph immediately as well as the full view photograph after the specified delay. Participants then completed 8 practice trials on their own. The occlusion levels and delays for the example and practice trials were predetermined but the photographs that served as reward were randomly selected from the aforementioned bank of pictures.To promote participant engagement, following every five trials a screen appeared asking participants to rate their subjective experience during the last viewed photograph using a Likert scale ranging from extremely unpleasant (-4) to extremely pleasant (+4). After a rating was entered, a screen labeled “Processing Data” appeared, with a screen-wide loading bar that progressively filled in. The wait time during that screen was designed to equalize experimental time across participants: it lasted five seconds plus the duration of all non-chosen delayed options during the previous five trials. Participants were not informed of the rationale for this “Processing Data” screen, but were told during instructions that their decisions would not impact the duration of the task or the number of photographs that they would view. This procedure insured that choosing the immediate viewing option would not result in seeing more pictures or completing the task sooner, an experimental confound that has been related to increased discounting in humans . Task duTo evaluate the subjective reward value of viewing photographs occluded by lines, participants were administered a pleasantness rating task . ParticiThe hypothetical task involved a series of hypothetical decisions between varying amount of money “Now” and $100 after varying delays . PossiblTM Psychtoolbox-3 [All tasks were programmed and displayed using the Matlaboolbox-3 , and admState and trait anxiety were measured using the State Trait Anxiety Inventory . This inM is the objective value of the reward, k is the discounting rate, and T is the delay. Because the value of the delayed reward was kept constant, that value was normalized to M = 1. Minimum subjective values were SVmin= $1 in the hypothetical task and SVmin= 13% of visible photograph in the experiential task. The SVs were transformed to set the minimum subjective value to 0, as assumed in the hyperbolic model:To evaluate whether the experiential intertemporal choice task yielded valid delay-reward tradeoff, pairs of indifference points obtained for each delay and each participant were fit to a model of reward subjective values (SV) decreasing hyperbolically with increasing delay :SV=M1+kR2, and the second evaluated model fit using linear mixed modeling. For the first analysis, best fit hyperbolic curves were first calculated for each participant using least square fit, implemented using the fmincon minimization function of MatlabTM. R2 values were then computed, that quantify the proportion of variance additionally explained by the model compared to the mean of the participant’s indifference points:SSR represents the sum of squares of the model’s residuals and SSTot represents the variance about the data’s mean. Negative R2 values suggest that the data are better described by the data’s mean. Consistent with previous work [R2 values across the experiential and hypothetical tasks.Model assessment was carried out by means of two complementary analyses: the first evaluated amount of tradeoff between delay and reward in each individual separately through calculation of ous work , we repoR2 is not appropriate as it confounds model fit with discounting rate [R2 value. Hyperbolic fit was evaluated instead using linear mixed modeling with participant as a random factor. This analysis allows fitting the indifference data points of all participants at once, thus simultaneously taking into account within and across subject variance. It also provides a test of significance of the hyperbolic model fit compared to the null model defined by separate means for each participant that takes into account the different number of parameters across models. The model was constructed using algebraic reformulation of Eq , using ing rate . That ison of Eq  into a lYij represents the transformation of the subjective value ith participant and jth delay, such that Tj is the log-transform of the jth delay. (Log base e is assumed throughout the paper). The model implicitly includes the discounting rates log k as intercepts (βi0), determined for every participant (random effect) and on average for the group (fixed effect). The regression coefficient associated with log Tj was fixed to 1. Model fit was carried out using maximum likelihood as implemented in the lme4 package [Yij = βi0. Model fit was evaluated using the Akaike’s Information Criterion (AIC) [Rsquared effect size was estimated using the method developed by Nakagawa & Schielzeth [piecewiseSEM R package. Model comparison was carried out using a Likelihood Ratio Test with χ2-distribution. Goodness of fit was also evaluated for each participant separately from the least square fit results by calculating the root mean square error (RMSE), which quantifies the average distance between the model and the data independently from the data’s mean:RMSE in the context of temporal discounting).The linear mixed model was defined as: package  of R [88on (AIC)  and Bayeon (AIC) . Rsquarehielzeth , implemeint  and on average for the group (fixed effects). The logistic model was tested on experiential and hypothetical indifference point data and compared to the hyperbolic model using the AIC and BIC indices of fit, Rsquared effect size, and Likelihood Ratio Test. Again, the likelihood ratio test provided a test of significance that permitted comparison of model fit, taking into account the different number of parameters across models. RMSE was also calculated for each participant separately for an indication of individual goodness of fit.The model implicitly includes the negative product of parametersPleasantnessij represents the rating of pleasantness experienced by participant i after viewing a partially occluded photograph j, Occlusionj is the level of occlusion of that photograph, and regression coefficient βi1 is included both as fixed and random effects. The model also included fixed and random intercepts, βi0. Model fit was tested against a null model, where pleasantness ratings could be different on average for each participant, but remained constant as a function of occlusion: Pleasantnessij = βi0. Model comparison was carried out using the AIC and BIC indices of fit, Rsquared effect size, and Likelihood Ratio Test. Pearson’s product moment correlations between pleasantness ratings and occlusion levels were also calculated for each participant, with absolute values used as input in subsequent analyses to model individual differences in reward sensitivity when viewing partially occluded photographs.To examine the association between level of occlusion of the photographs and experienced reward in the pleasantness rating task, linear mixed modeling was carried out with participant as random factor. The model was defined as follows:We also examined the relationship between levels of occlusion and pleasantness ratings given following every five trials during the intertemporal choice task. This analysis was limited by the occlusion levels chosen by participants but can arguably provide more direct insight into participants’ reward experience while making intertemporal decisions. We used the same linear mixed model as Eq , but becAUC [AUC indicates greater willingness to wait. We used AUC rather than the discounting parameter k, because it captures the entire shape of the indifferent point curve. AUC is usually calculated by drawing trapezes between indifference points and the x-axis, and by summing the trapeze areas together. However, because this model-free technique can be disproportionately affected by noise in the data, we opted to derive a model-based AUC by carrying out a preliminary fit of the data with the two-parameter logistic model described above (using the least-square fit results), and by integrating this curve over the delay interval. The relation between experiential AUC and hypothetical AUC was tested using Pearson’s product moment correlation. The Bayes factor test for linear correlation was also carried out to quantify evidence in favor of the null hypothesis. This test was implemented with the R BayesFactor package [To evaluate the relation between experiential and hypothetical temporal discounting, we first computed measures of discounting for each participant and each task using area under the indifference points curve, AUC , where g package , using aAUC and hypothetical AUC. The second analysis used the same model with the addition of reward sensitivity  as possible mediator for the effect of state anxiety on experiential AUC. Both models included parameters for the variances of state anxiety and trait anxiety, covariance of state anxiety with trait anxiety, residual variances of experiential AUC and hypothetical AUC, and residual covariance of experiential AUC with hypothetical AUC. Parameters were estimated using maximum likelihood with the R lavaan package [The effects of state and trait anxiety on performance in experiential and hypothetical tasks were simultaneously examined using path analysis. A first path analysis used state and trait anxiety as predictors of experiential  package . Standar package , Root Me package , and Sta package .RMSE = 0.131 (SD = 0.080). Median R2, representing the amount of variance accounted for compared to the mean of the indifference points was 0.520. For 7 out of 44 participants (15.9%) the hyperbolic model did not explain more variance than the mean of the participant’s indifference points. Examination of individual indifference point data suggested exclusive preference of the delayed reward in 3 participants, generally consistent choice of the delayed option with some variability in 3 participants, and seemingly random responding in 1 participant. Linear mixed modeling using the hyperbolic model on all participants simultaneously revealed a model fit  that was better than that of the null model , with difference in fit quality that was significant (χ2(0) = 177.2, p < .001). The intercept in the hyperbolic model, corresponding to the average log-discounting rate log k, was estimated to be β0 = -6.7 (standard error SE = 0.8). Taken together, these results validate the presence of a delay-reward tradeoff for most participants during the experiential intertemporal choice task, with the hyperbolic shape providing better approximation than the mean of the indifference points.Least square fit carried out using the hyperbolic model on the experiential indifference points of each participant yielded mean average residual error RMSE = 0.132 (SD = 0.041) and median R2 = 0.806. For one participant the mean provided a better fit. For reference, McKerchar and colleagues [R2 of 0.929 for the hyperbolic model and found that the mean provided a better fit for 10 out of 64 individuals (16%). Linear mixed modeling further confirmed that the fit with the hyperbolic model  was better than that with the null model , with a difference in fit quality that was significant (χ2(0) = 632.3, p < .001). The intercept in the hyperbolic model was estimated to be β0 = -9.0 (SE = 0.4).Least square fit carried out using the logistic function model on the hypothetical indifference points yielded mean average residual error lleagues  reportedRMSE (t(43) = 0.136, p = 0.892, Cohen’s d = 0.021), but less variance explained compared to the mean in the experiential data . This difference reflects the larger proportion of individuals who displayed consistent to almost consistent choice of the delayed option in the experiential task (poor R2 but good to excellent fit).A summary of the fit results is presented in RMSE = 0.102 (SD = 0.067) and median R2 = 0.657  that was significantly better than the hyperbolic model (χ2(3) = 494.5, p < .001). The estimates of the fixed effect regression coefficients were β0 = -13.5 (SE = 0.7) and β1 = 4.3 (SE = 0.4), the latter corresponding to the average estimate of parameter a.Least square fit carried out using the logistic model on the experiential indifference points of each participant yielded mean average residual error RMSE = 0.114 (SD = 0.041) and median R2 = 0.850. There was no participant for whom the logistic function did not explain more variance than the mean of the participant’s indifference points. For reference, McKerchar and colleagues [R2 of 0.963 for the Rachlin’s power function model, a model equivalent to the logistic function model, and had no individual for whom the mean provided a better fit. Linear mixed modeling revealed model fit using the logistic function model  that was significantly better than that with the hyperbolic model (χ2(3) = 330.6, p < .001). The estimates of the fixed effect regression coefficients were β0 = -12.4 (SE = 0.6) and β1 = 1.8 (SE = 0.1).Least square fit carried out using the logistic function model on the hypothetical indifference points yielded mean average residual error lleagues  reportedRMSE (t(43) = 1.031, p = 0.308, Cohen’s d = 0.155), but less variance explained compared to the mean in the experiential data . This difference again reflects the larger proportion of individuals who displayed consistent to almost consistent choice of the delayed option in the experiential task (poor R2 but good to excellent fit).Example indifference point datasets obtained for two participants during the experiential intertemporal choice task are presented in β = -0.55, t (44.1) = 18.1, p < .001). The fit of the model with occlusion levels as fixed and random effects  was better than that of the null model , and the difference in model fits was significant (χ2(3) = 2221, p < .001). Pearson’s product moment correlations calculated separately for each participant averaged r = -0.73 (SD = 0.16) and were significant (p < 0.05) for all but one participant. The absolute values of the correlations between photograph occlusion and pleasantness ratings were used to model individual differences in reward sensitivity in the path analyses.The relation between photograph occlusion level and pleasantness ratings is illustrated in β = -0.39, t (554.9) = 16.0, p < .001). The fit of the linear mixed model with occlusion levels as fixed effect  was better than the null model  and the difference in model fits was significant (χ2(1) = 213.0, p < .001). These findings suggest that participants as a group paid attention to the photographs and experienced them as more pleasant when they were less occluded.Analysis of the pleasantness ratings collected during the intertemporal decision task also demonstrated a significant negative effect of occlusion level .The Pearson product moment correlation between experiential CFI   =  1.0, RMSEA < .001, SRMR = .021). State anxiety and trait anxiety were significantly correlated . Participants reported slightly less state anxiety  = -2.78, p = 0.007, Cohen’s d = 0.406) and reported levels of trait anxiety  = 1.54, p = 0.130, Cohen’s d = 0.248). State and trait anxiety displayed distinct relations to experiential and hypothetical AUC, where greater AUC implies greater willingness to wait. State anxiety had a negative effect on experiential AUC  but no significant effect on hypothetical AUC . Trait anxiety had a positive effect on experiential AUC . Its effect on hypothetical AUC did not reach significance but was noted to be numerically negative . Explanatory variables accounted for 15.0% of the variance in experiential AUC and 5.9% of the variance in hypothetical AUC. Of note, the correlations of state anxiety with experiential AUC  and trait anxiety with experiential AUC  were not significant when considered in isolation. These results highlight the presence of an interaction between state and trait factors, which is accounted for by the path analysis. Linear regression on experiential AUC confirmed significance of a model including state anxiety, trait anxiety, and their interactions as regressors  = 4.8, p = 0.006, R2 = 0.26), with a significant state by trait anxiety interaction . This interaction is illustrated in AUC that decreased (less willingness to wait) with increasing state anxiety ; while individuals with higher trait anxiety displayed experiential AUC that remained high, independent of their state anxiety .The path analysis model without mediation  tha range =   thaCFI  =  1.0, RMSEA < .001, SRMR = .018). State anxiety had a negative effect on reward sensitivity , which itself had a positive effect on experiential AUC . The direct effect of state anxiety on experiential AUC was no longer significant , suggesting complete mediation through reward sensitivity. The effect of state anxiety on hypothetical AUC remained the same, and was non-significant . Trait anxiety had a non-significant effect on reward sensitivity , but still had a positive effect on experiential AUC . Its non-significant effect on hypothetical AUC remained the same . Explanatory variables accounted for 12.9% of the variance in reward sensitivity, 39.3% of the variance in experiential AUC and 5.9% of the variance in hypothetical AUC.The path analysis model with mediation /s. Consistent with Stevens’ psychophysical power law [a (or s) may be interpreted as variability in the subjective perception of time [a in the experiential compared to hypothetical intertemporal choice tasks, a is likely to be both individual- and task-dependent.A logistic function interpretive framework was also proposed, providing superior fit of temporal discounting indifference points compared to the classic hyperbolic model , 61. Thehe curve . Furthernt model , 66, 67.ower law , parametc, characterizing the asymptote at long delays, was also entertained. Such a parameter could be interpreted as the minimum amount of reward that might appear worth obtaining for a given person. For example, if $5 is considered a negligible amount of money by an individual, they might decide that it is worth waiting even 50 years for the possibility of $100, rather than getting $5 now. In other words, their asymptote may be $5 instead of $0, as assumed by the two-parameter model. Testing of model fit revealed improvement over the two-parameter logistic model that was negligible in size and not significant  = 1.354, p = 0.183). The more complex three-parameter model was thus discarded for parsimony.The possibility of adding a third logistic function parameter, Comparison across experiential and hypothetical choice tasks revealed that measures of temporal discounting were not correlated, suggesting the presence of distinct underlying mechanisms. Although the possibility that a weak correlation could be detected in a larger sample of participants cannot be excluded, based on the Bayes factor test, such possibility is three times less likely than a null correlation. Moreover, based on the effect size in the current sample , such correlation would likely be extremely small to negligible compared to correlations between hypothetical tasks reported in previous studies , whThe effects of trait anxiety were more complex. Greater trait anxiety was numerically, albeit non-significantly, associated with increased discounting in the hypothetical task. This association was weaker than that seen in some prior studies –77 but cBy taking into account both trait and state anxiety in one model, we were able to isolate their respective effects. Yet, our results also demonstrate that these variables interact, highlighting the importance of considering their joint effects on discounting. Notably, we show that the significant increase in experiential discounting observed with greater state anxiety only applied to individuals with lower trait anxiety. Individuals with higher trait anxiety appeared more willing to wait across the board, independently of their state anxiety. This pattern may suggest that trait anxious individuals are less influenced by current experience, and that instead, their choices remain governed by consideration of abstract principles. This notion is also supported by the absence of mediation by reward sensitivity of the association between trait anxiety and experiential intertemporal choice.Interactions between state and trait anxiety have been reported in previous studies, with similar findings that state anxiety (or induced stress) yields increased discounting in individuals with low but not high trait anxiety (or trait perceived stress) , 107. OfThe observed behavioral differences between hypothetical and experiential intertemporal choice may stem from differences in two distinct components of choice: valuation  or deliberation  , 111. InDifferences in behavior across the experiential and hypothetical tasks may also reflect differences in deliberative processes. In hypothetical intertemporal choice, because all decisions are made before consequences can be experienced, deliberation can be carried out conceptually, relying solely on semantic knowledge and reasoning. By contrast, in experiential tasks, choices may initially be based on semantic knowledge and reasoning but can be revisited based on the experience of the delays and rewards during the task. That is, participants can sample from past experience to mentally evaluate possible outcomes and weigh them against each other, a process also demonstrated to rely on the hippocampus –120. ThiAlthough hippocampal involvement has been reliably demonstrated in animals –19, it hBecause of experimental constraints, the experiential and hypothetical intertemporal choice tasks necessarily differed not only in the experience of delays and rewards, but also in the time scale of the delays (seconds versus days to years), the costs incurred by the delays, and the nature of the rewards. Differences in time scale are unlikely to explain our findings, as evidence suggests that subjective value brain signals during intertemporal choice tasks adapt to the range of values employed in the experimental context , and corThe use of consumable perceptual rewards in the experiential task compared to money in the hypothetical task may also have contributed to differences in discounting across our tasks. Within the context of hypothetical intertemporal decisions, several studies have documented steeper temporal discounting of consumable rewards  compared to money , 34, 39 We measured state anxiety at the beginning of the session, but it is possible that changes in participants’ inner state took place over the course of the session, in part depending on their personal experience of photograph content. Exposure to pictures of nature scenes, compared to pictures of buildings or geometric shapes, has been associated with decreased hypothetical discounting –125. GivSimilarly, the current study did not comprise ongoing measurement of reward consumption. The measure of reward sensitivity was indirect, based on pleasantness ratings that were subjective and measured after the intertemporal choice task. For a more direct and unbiased assessment of reward consumption, future studies may consider use of online psychophysiological measures such as eye-tracking.Finally, participants in our study were all female college students. This sample promoted homogeneity for consideration of underlying mechanisms; however, generalizability of findings to males remains to be established. Effects of gender on hypothetical intertemporal choice have been mixed –128, witThe present study employed an experiential intertemporal choice task using artistic photographs as consumable perceptual reward. To fit indifference point data, a two-parameter logistic function interpretive framework was proposed that accounts for individual variability not only in the delay at which an individual tends to switch from consistent choice of the delayed option to consistent choice of the more immediate option, but also in the slope of that switch.Our findings provide support for the notion that experiential and hypothetical intertemporal choices are mediated by distinct mechanisms. Performance across the two tasks was not correlated, and both state and trait anxiety were significantly related to the experiential task but not to the hypothetical task. The involvement of distinct mechanisms in the experiential compared to hypothetical task aligns with neural evidence for the recruitment of the hippocampus in animal but not in classic human intertemporal choice.


This study conducted de novo sequencing of multiple double-stranded (ds) RNA (dsRNA) elements that were obtained from fungal viruses infecting two Fusarium sambucinum strains, FA1837 and FA2242, using conventional HTS and long-read direct RNA sequencing (DRS). De novo assembly of the read data from both technologies generated near-entire genomic sequence of the viruses, and the sequence homology search and phylogenetic analysis suggested that these represented novel species of the Hypoviridae, Totiviridae, and Mitoviridae families. However, the DRS-based consensus sequences contained numerous indel errors that differed from the HTS consensus sequences, and these errors hampered accurate open reading frame (ORF) prediction. Although with its present performance, the use of DRS is premature to determine viral genome sequences, the DRS-mediated sequencing shows great potential as a user-friendly platform for a one-shot, whole-genome sequencing of RNA viruses due to its long-reading ability and relative structure-tolerant nature.An increasing number of viruses are continuously being found in a wide range of organisms, including fungi. Recent studies have revealed a wide viral diversity in microbes and a potential importance of these viruses in the natural environment. Although virus exploration has been accelerated by short-read, high-throughput sequencing (HTS), and viral  Mycoviruses infect all taxonomic groups of fungi with a surprisingly wide diversity . Most my−3 to 10−5 mutations per copied nucleotide, and the resultant aggregated replica makes it difficult to determine the entire genome sequence  generate populations of closely related viruses which are generally referred to as “quasispecies.” The error rate of nucleotide incorporation in RNA viruses is estimated to be 10sequence . Thus, msequence , and sucsequence . This posequence .Recent advances in long-read sequencing technology from Oxford Nanopore Technologies may have the potential to overcome these problems. The portable sequencer (MinION) is a single-molecule DNA/RNA sequencing device that directly recognises native, individual nucleic acid molecules. It does so by reading the sequence of a single-stranded nucleic acid molecule passing through a flow cell-mounted nanopore as disruptions of current across a membrane. This enables direct sequencing of RNA molecules without the need for RNA reverse transcription or PCR amplification. The genome size of currently known RNA viruses is no more than 41 kb . In thisde novo viral genomic sequences from pre-set dsRNA molecules of fungal origin. The results reveal seven reconstructed viral contigs representing novel mycoviral genome sequences and raise strengths and limitations of each sequencing technology. We further discuss the potential of the use of DRS for viral RNA characterisation; it is possibly useful technical updates, as well as newly characterised mycoviruses.RNA viruses contain dsRNA as genomic dsRNAs or as replication intermediate forms in infected cells. These viral dsRNA molecules can be easily purified by cellulose column chromatography, which is an efficient technique to separate virus-associated RNA fractions from host RNA species. In this study, we compare the performance of DRS and Illumina HiSeq in generating Fusarium boothii strain BL13 was previously isolated from the Fusarium head blight-infested wheat sample in Ethiopia . Fungal isolates were maintained on synthetic low nutrient agar or potato dextrose agar medium at 20°C and long-term stored at 4°C. For dsRNA extraction, fungal mycelial plugs were inoculated into potato dextrose broth liquid medium and incubated for a week at 20°C without agitation.Ethiopia . This stFiltrated mycelia were homogenised in the presence of liquid nitrogen, and the total RNA fractions were obtained by treatment with one round of phenol, phenol:chloroform:isoamyl alcohol (25:24:1), and chloroform:isoamyl alcohol (24:1) sequential extraction. dsRNAs were further isolated from the total RNA fractions using Cellulose Powder C . To eliminate fungal chromosomal DNA and single-stranded RNA (ssRNA) species, the dsRNA fractions were further treated with RNase-free RQ1 DNase I and S1 Nuclease .Escherichia coli Poly(A) Polymerase following the manufacturer’s protocol . The polyadenylated RNA was then purified using Agencourt RNAClean XP kit  and subjected to library preparation. The RNA library was loaded on the MinION flow cell for sequencing. DRS was performed on a single R9.4/FLO-MIN106 flow cell for 2–18 h.The viral RNA library was prepared following the manufacturer’s protocol with minor modifications . A total of 360 μl of dimethyl sulfoxide (DMSO) were mixed with a 40-μl solution containing 1 μg of viral dsRNA. The dsRNA was denatured into ssRNA by incubating the mix for 20 min at 65°C. The denatured viral RNA was polyadenylated using The cDNA library was constructed following the NEBNext Poly(A) mRNA Magnetic Isolation Module protocol (NEB). A total of 200 ng of viral dsRNA diluted in 13-μl of nuclease-free water were mixed with 4 μl of 10x first-strand cDNA synthesis buffer and 1 μl of random primer, and the mix was then incubated at 94°C for 15 min. The sample was immediately placed on ice, and 2 μl of NEBNext First Strand Synthesis Enzyme Mix was added. The sample was then incubated at 25°C for 10 min, 42°C for 15 min, and 70°C for 15 min for first-strand cDNA synthesis. Second-strand cDNA was synthesised by following the protocol for NEBNext Poly(A) mRNA Magnetic Isolation Module (Chapter 1.4–1.6). Illumina HiSeq (paired-end 85 bp) was used for sequencing, and the resulting sequence data were deposited in the DDBJ Sequence Read Archive at the DNA Data Bank of Japan (DDBJ)De novo assembly was conducted using Minimap2 version 2.17-r941 and Miniasm version 0.3-r179  and a gene-specific primer set from given dsRNA fragments. cDNA amplification was done with DNA polymerases, such as PrimeSTAR  or GO-Taq .The terminal sequences of dsRNAs were determined by the following method. Pre-denatured dsRNAs in DMSO  were ligated at their 3'-ends with a 5'-phosphorylated oligodeoxynucleotide, 3'-rapid amplification of cDNA ends (RACE) adaptor (5'-CAATACCTTCTGACCATGCAGTGACAGTCAGCATG-3') using T4 RNA ligase (Takara) at 16°C for 16 h. Ligated DNA-RNA strands were DMSO-denatured in the presence of the oligonucleotide 3'-RACE-1st (5'-CATGCTGACTGTCACTGCAT-3') and used as templates for cDNA synthesis. The resulting cDNA was further amplified by secondary PCR with 3'-RACE-2nd (5'-TGCATGGTCAGAAGGTATTG-3'), and gene-specific primers were designed for the desired targets.E. coli strain DH5α or TOP10 for Sanger sequencing analyses. Plasmid clones were used for BigDye sequencing  on a 3,100-Avant sequencer  following the manufacturer’s instructions.The obtained cDNA fragments were cloned into the pGEM-Teasy  or pCR-Blunt cloning vectors . These were used for transformation of Sequence homology searches were performed using the Basic Local Alignment Search Tool (BLAST) algorithm provided by the National Center for Biotechnology Information,Multiple amino acid (aa) alignment was constructed using MAFFT version 7Fusarium sambucinum strains FA1837 and FA2242 were isolated from a Japanese Fusarium collection as dsRNA-positive isolates (unpublished data). Agarose gel electrophoresis revealed that FA1837 accumulated a single dsRNA band with more than 10 kbp, and FA2242 carried multiple dsRNA bands ranging from 2.5 to over 10 kbp . BLASTX analysis of this sequence revealed that it had the highest identity (25.83%) with the polyprotein encoded by a member of the family Hypoviridae, namely Fusarium graminearum hypovirus 1  was 10,380 nt long and had the highest identity (29.36%) to the polyprotein encoded by Fusarium oxysporum dianthi hypovirus 2. Contig 3 was 5,119 nt long and showed similarity to the RdRp and coat protein (CP) of Botrytis cinerea victorivirus 1  showed a significant similarity to a viral factor in the BLASTX search, which is a hypothetical protein encoded by FgHV1 with 39.06% aa identity  and one putative CP sequence  based on the contigs generated from DRS and Illumina reads was performed. To predict the mitovirus sequences, the mitochondrial codon table was applied, whereas for the other sequences, the standard codon table was used. Well-established ORFs were predicted from all Illumina contigs, whereas no obvious ORFs were predicted in the DRS contigs. For example, in the FA1837 hypovirus, one large ORF was predicted from one Illumina contig (Contig 8); however, many small ORFs interrupted by stop codons were predicted from the corresponding DRS contig , and a helicase ATP-binding domain – were predicted to be present in this order from the N- to the C-terminus of this putative polyprotein. Besides those domains, a conserved domain with an unknown function named DUF3525 was also predicted upstream of the RdRp domain. Alphahypoviruses were classically distinguished from betahypoviruses by the number of ORFs they contain  and Wuhan insect virus 14 (WhIV14)], whereas the classical members have a small ORF encoding a protease in addition to a large polyprotein ORF  required for autoproteolytic activity and the putative cleavage site (Gly253) were conserved only in the protease domain of the large polyprotein  was performed .Next, the aa sequence alignment of the putative RdRp domain of the FA1837 hypovirus and other members of the tionship . An ML performed . The reses ICTV; . Hence, F. sambucinum hypovirus 2 (FsamHV2) based on the above-mentioned homology search. Moreover, the loss of >10 kbp dsRNA in FA2242  in FA2242 was not completed and its taxonomic placement was uncertain, the FA2242 hypovirus was tentatively named n FA2242 ,B was con FA2242 , thus thn FA2242 .Victorivirus genus members were the CP of BcVV3 (46.83%) and the RdRp of MoV1 (42.69%). The CPs of victoriviruses generally have an Alanine-Glycine-Proline-rich region on their C-terminal region and, indeed, this feature was also detected on the CP of the FA2242 victorivirus, especially on the most downstream 50 aa  and represents a potential novel species in the Victorivirus genus.Refining victorivirus Contigs 9 and 10 in the FA2242 strain revealed a full-length dsRNA genome sequence with 5,069 nt (accession number LC596824). The genome consists of 194 nt 5'-UTR, 2,274 nt CP-ORF, 2,544 nt RdRp-ORF, and 58 nt 3'-UTR , and itsam 50 aa . Moreoveipeptide . The famniavirus . Among t species ,C. Basedthan 60% . BecauseF. sambucinum mitovirus 1 (FsamMV1); Contig 12, FsamMV2; Contig 13, FsamMV3; Contig 14, FsamMV4; and Contig 15, FsamMV5 (accession numbers LC596825–LC596829). As commonly seen in the genomes of mitoviruses, the FsamMV contigs showed a relatively low G + C content (28.09–38.96%). Furthermore, the FsamMV replicases have an aa length and molecular mass of 783 aa and 89.12 kDa (FsamMV1), 777 aa and 88.85 kDa (FsamMV2), 771 aa and 89.84 kDa (FsamMV3), 707 aa and 79.93 kDa (FsamMV4), and 694 aa and 79.68 kDa (FsamMV5). A multiple alignment of RdRp domain encoded by the FsamMVs and selected Mitovirus members revealed that the replicases of all FsamMVs have six conserved motifs with the core GDD tripeptide  and short-read (Illumina HiSeq) sequencing methods. While both techniques succeeded in reconstructing nearly full-length viral genomes, the DRS did not retrieve any viral contig sequence with sufficient accuracy that is good enough for the ORF prediction. Based on the short-read sequencing, seven mycoviruses have been characterised, i.e., one hypovirus and one victorivirus  and five mitoviruses, of which the complete genome sequences were determined for FsamHV1 and FsamVV1. To the best of our knowledge, this is the first report of mycoviruses identified in F. sambucinum. The comparison of the sequencing efficiency between Illumina HiSeq and DRS revealed that the DRS technology is still on a developing curve to achieve the determination of viral genomic sequences by de novo assembly. Here, we discuss the performance of the DRS technology in this study and the potential solutions for the future application of DRS to dsRNA sequence determination.In this study, we conducted de novo assembly with its present performance. In this study, we attempted to overcome these sequence errors by enriching the read depth with a selective template  that is exclusive of host-associated RNA species and by refining contigs with available bioinformatics tools , virologists have only used DRS to detect viruses in clinical samples, to analyse the RNA modification of viral genomes, and to investigate complex viral genomic structures . This meools see . Even thools see . Neverthools see , it is ain vitro. It is also possible that the library construction was inhibited by insufficient dsRNA denaturation or re-hybridization of denatured RNAs or both. Considering the fact that a severe degradation of dsRNAs was not observed after the denaturation step (data not shown), the latter reasons seem more likely.The average length of DRS reads obtained in this study (672.5 nt) was significantly shorter than those reported in other studies. The plausible reason is the use of different RNA templates: we used dsRNA molecules in this study, whereas previous studies relied on ssRNAs . BecauseRNA viruses often carry poly(A) tails at the 3'-end. This modification is present in the dsRNA, either as a dsRNA genome (such as in partitiviruses) or as a replication intermediate of an ssRNA genome (such as in hypoviruses). We here found a strong bias of reads at the 3'-end of FsamHV1, and to some extent, of FsamHV2 . This isFinally, the UTRs of RNA viruses generally carry important cis-elements that form secondary/tertiary structures or distant base-pairing or both. Comparing the 5'- and 3'-ends of the FsamHV1 and FsamVV1 complete genomes  with those of the DRS contigs, we observed that all of the termini sequences of DRS and Illumina contigs were longer than those of the complete genomes, suggesting a high variation of terminal sequences in the viral genomes . BecauseContamination of host-derived reads has been a major problem for DRS application in virus sequencing. Therefore, the use of purified viral RNA elements as DRS templates poses a great advantage to specifically recover viral reads. In this regard, viral genomic RNA purified from virions resulted in a high yield of viral DRS reads by limiting the contaminated host read to ~60% . Likewisde novo assembly of FsamVV1 (FA2242) with Illumina short reads, the obtained contigs were divided at the boundary of two ORFs , or by coupled translation termination-re-initiation as two independent proteins  contain two ORFs (A and B): the ORF A of CHV1 encodes the p29 cysteine protease, which functions as an RNA silencing suppressor, and also p40, which is cleaved by p29-autocatalitic activity; the downstream ORF B encodes the replication-associated polyprotein, which corresponds to the protein conserved in all hypoviruses , which promote the initiation of protein synthesis by cap-independent non-canonical mechanisms  can be found at: NGS data (DRA011337) and accessions LC596823–C596830.CR, FF, and SC: designed the research and obtain research funds. FF: provided the research materials. YM, AO, MC, and TS: executed the experiments. YM, KU, MC, FF, and SC: performed the data and bioinformatic analyses. YM, KU, and SC: wrote the manuscript. FF and SC: edited the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Self-rated health (SRH) is a good predictor of morbidity and mortality. Extensive research has shown that females generally report poorer SRH than males but still tend to live longer. Previous studies used cross-sectional or pooled data for their analyses while ignoring the dynamic changes in males’ and females’ SRH statuses over time. Furthermore, longitudinal studies, especially those that focus on older adults, typically suffer from the incompleteness of data. As such, the effect of dropout data on the trajectories of SRH is still unknown. Our objective is to examine whether there are any gender differences in the trajectories of SRH statuses in Chinese older adults.The trajectories of SRH were estimated using the pattern-mixture model (PMM), a special latent growth model, under non-ignorable dropout data assumption. We analyzed the Chinese Longitudinal Healthy Longevity Survey (CLHLS) data of 15,613 older adults aged 65 years and above, collected from 2005 to 2014.The results demonstrated the effect of non-ignorable dropout data assumptions in this study. The previous SRH score was negatively associated with the likelihood of dropping out of the study at the next follow-up survey. Our results showed that both males and females in China perceive their SRH as decreasing over time. A significant gender difference was found in the average SRH score  in this study. Nonetheless, based on the results obtained using the PMM, there are no gender differences in the trajectories of SRH at baseline as well as in the rate of decline among the total sample. The results also show that males and females respond to SRH predictors similarly, except that current drinking has a more pronounced positive effect on males and healthcare accessibility has a more pronounced positive effect on females.Our results suggest that missing data have an impact on the trajectory of SRH among Chinese older adults. Under the non-ignorable dropout data assumptions, no gender differences were found in trajectories of SRH among Chinese older adults. Males and females respond to SRH predictors similarly, except for current drinking habit and healthcare accessibility.The online version contains supplementary material available at 10.1186/s12877-021-02484-4. The world is rapidly aging. It is predicted that the proportion of people aged 60 and above in the global population will double from 11 % to 2006 to 22 % by 2050. The rapA large body of life-cycle analysis research has shown that females consistently report worse SRH than males, yet still tend to outlive them–12. HowePrevious studies have used cross-sectional data or pooled data to generalize various patterns of gender differences in SRH. Extensive research has shown no gender differences in SRH of older adults, 13–16. For a decade, an increasing number of longitudinal studies on health inequalities have also been carried out. These studies with two and more time points have shown a slow decline in SRH trajectories across adulthood–28. HoweMost of the previous studies on the trajectory of gender differences were based on the experience of developed countries, so there is insufficient research on gender differences in developing countries. Furthermore, longitudinal studies, especially those that focused on older adults, typically suffer from the incompleteness of data. Previous longitudinal studies often assumed a missing at random (MAR) mechanism, and they excluded cases with missing data directly for analysis. However, there are many situations in which dropouts are missing not at random (MNAR), especially in research related to older adults, because participants might have died during the study or were too frail to participate in follow-up surveys. When asTo our knowledge, few studies have examined the longitudinal association between gender and SRH among Chinese older adults. Therefore, this study is crucial in the fight against health inequalities among older adults, which aims to examine gender differences in the trajectories of SRH statuses in Chinese older adults. This study uses data from the CLHLS to examine the following questions: (1) Do the missing data have an impact on the gender trajectory of Chinese older adults? and (2) Do SRH trajectories vary by gender among Chinese older adults?N = 15,613 in 2005, with follow-up interviews completed by 7452 participants in 2008, 4178 in 2011, and 2777 in 2014). Details regarding the study sample are shown in Fig. Publicly available data from the CLHLS were used in this study. CLHLS collected information about older adults aged 65 and above regarding their health condition, socioeconomic characteristics, lifestyle, health status, quality of life, mental attitude, daily functioning, health service accessibility, and so on, across 22 provinces in China from 1998 to 2014. The parSRH is essentially a subjective measure involving complex perceptions of multiple health-related areas, which tBased on previous studies, 46, 47,Stata 15.1 was used to complete the descriptive statistics. The latent growth model (LGM) analytic approach Fig. , which wWe undertook four steps to examine our assumption, as follows: (1) Descriptive statistics of SRH were computed, including mean and standard variance. (2) The mean plots for the sample and estimated means were calculated to determine the shape of the growth curve Fig. . A lineaThe following three sensitivity analysis methods were used to test the robustness of the results. We considered “unable to answer” as being designed for participants who were too frail to answer the self-rated question in CLHLS. First, For handling the missing data, two methods were introduced: (1) replacing missing values of independent variables with non-missing values of the previous year and (2) using maximum likelihood estimation under MNAR to reduce the potential bias from missing data.In total, 15,613 older adults  aged 65 to 120 years old were included in our study at the baseline. Given that the CLHLS was specially designed by considering the clusters of age-sex residence , the weight variable was applied to calculate the descriptive statistics for the whole elderly population in the sampled provinces. After cP < 0.001; 2008: P < 0.001; 2011: P < 0.001; 2014: P = 0.005).A significant gender difference was found in the average SRH of all four waves of data  Fig. . The meaIn addition, we found a gender difference in the socio-structural factors, behavioral health factors, and health status factors except for healthcare accessibility and residence. A description of the full sample and subgroups can be found in Table 2/df. As a result, the quadratic growth model best fits our data. Taking into account that poor SRH could lead to the dropout of each participant, the dropout indicator was added to the quadratic growth model to construct the PMM.We performed model selection based on the change trend of the four-wave SRH mean value of the full sample  Fig. . We examβ = -0.054 (95 %CI:-0.082~-0.027), P < 0.001], the lower SRH at 2008 could be at a high risk of dropout at 2011 [β = -0.130 (95 %CI:-0.171~-0.089)], P < 0.001], except for the fact that the SRH at 2011 was not associated with the dropout at 2014.Table β = 0.033 (95 %CI: -0.055 ~ 0.121), P = 0.461]. In additional, gender  could not predict the slope  or quadratic  growth of SRH trajectories.For gender, the difference of SRH at baseline between male and female was not significant [For socio-structural factors, education could not predict the intercept, slope, or quadratic growth. However, age, income, and residence  were positively associated with SRH in four study periods expect the residence in 2011. As to lifestyle, smoking was positively associated with SRH in 2005, while drinking was positively associated with SRH in 2005, 2011 and 2014. We also noted that higher level of social activities may result in better SRH among the four study periods. For social relationship, living arrangement  was not associated with SRH in the four study periods, while marital status was only associated with SRH at 2005. For health status, ADL disability, IADL disability, and chronic diseases were negatively associated with SRH. For health services accessibility, adequate healthcare accessibility was positively associated with a better SRH.Table We found the gender difference as follows: First, drinking was positively associated with SRH, except for the year 2008 in the male subgroup, while drinking was positively associated with SRH only at 2008 in the female subgroup. Second, as to health services accessibility, adequate healthcare accessibility was positively associated with a better SRH in the four study periods in the female subgroup, and was only significant in 2008 and 2014 in the male subgroup.We conducted sensitivity analysis in three ways: (1) eliminating cases with “unable to answer” for SRH, (2) recoding the “unable to answer” to “very poor” for SRH, and (3) eliminating the lost to follow-up cases. As in our main results, gender could not predict the intercept, slope, or quadratic growth of SRH. The three sensitivity analyses showed the same results Table , which aThis study used a quadratic PMM to examine two questions: (1) Do the missing data have an impact on the gender trajectory of the Chinese older adults? and (2) Do SRH trajectories vary by gender among Chinese older adults? The data were from a national random sample of older adults aged 65 years and above across 22 provinces in China, collected from 2005 to 2014. Four main results can be discussed.First, this study supports the argument that gender differences in SRH trajectory among older adults needs to consider the impact of dropout data. Previous longitudinal studies based on older adults often did not explicitly illustrate the missing data, 31, 35,Second, under non-ignorable dropout data assumptions, no gender differences were found in trajectories of SRH among Chinese older adults. Nonetheless, the role of gender in SRH related longitudinal analysis research remains ambiguous, 55. ForThird, although there is no gender difference in the trajectories, the average SRH of females is lower than that of males. The present study showed that higher income, greater participation in social activities, age, current drinking, residence , and healthcare accessibility are positively associated with the SRH of older adults, while poor health status was negatively associated with both males and female SRH across almost every survey time point. Thus, social disadvantage might be an important reason for females’ poorer SRH. For example, a high SRH score is associated with a higher socioeconomic status, i.e., generally male tender to with more social resources, so they are more likely to be in good health status in our society, 56. GenFinally, performing the analysis by gender of the respondent, the results show that males and females respond to SRH predictors similarly. Education could not predict the intercept, slope, or quadratic of SRH; age, income, health services, and social activities are positively associated with both males and female SRH, while health status factors were negatively associated with both male and female SRH. The result is consistent with most studies on SRH trajectories in the general adult population or aging population, 29, 46.There were several limitations to this research. First, this study used only SRH measurement. Health indicators are multidimensional, including both objective and subjective factors. Hence, future studies should include objective measures to assess health based on gender. Second, psychosocial factors are also patterned according to gender. Peoples’ experiences of chronic stress and their level of psychological resources are rooted in the socio-structural context of their lives. Future studies should introduce psychological variables to test gender differences in health statuses. Third, this study was unable to eliminate the possibility of reverse causality. Although this study lagged variables when possible, it is possible that the SRH affected the covariates included in the analysis. For example, because changes in current drinking are taking place at the same time as changes in SRH, it is possible that changes in SRH influenced current drinking. Finally, interdisciplinary research needs to be strengthened, as health studies have failed to adequately explore the combination of social and biological aspects in the differences between male and female health statuses.The results of this study showed that (1) missing data had an impact on the gender trajectory of the Chinese older adults, and SRH was negative associated with the dropout (2) under non-ignorable dropout data assumptions, no gender differences were found in SRH trajectories among Chinese older adults (3) males and females respond to SRH predictors similarly, except for current drinking and health services. Based on these results, we make the following recommendations for future policymaking and service implementation efforts. First, the health level of older adults in China has shown a declining trend, so the government and the local care communities should provide more health services to meet their health needs. Second, public policies must continue to address the cause and consequences of the social disadvantages that older females face. Third, public policy makers should pay attention to the health needs of both males and females, who may be at an increased risk of disability and illness. Finally, the management of health status should be strengthened, the accessibility of health services should be improved, and gender inequality should be reduced since these factors are conducive to improving the health of both genders.Additional file 1:Appendix Table 1


Four-stranded G-quadruplex (G4) structures form from guanine-rich tracts, but the extent of their formation in cellular RNA and details of their role in RNA biology remain poorly defined. Herein, we first delineate the presence of endogenous RNA G4s in the human cytoplasmic transcriptome via the binding sites of G4-interacting proteins, DDX3X (previously published), DHX36 and GRSF1. We demonstrate that a sub-population of these RNA G4s are reliably detected as folded structures in cross-linked cellular lysates using the G4 structure-specific antibody BG4. The 5′ UTRs of protein coding mRNAs show significant enrichment in folded RNA G4s, particularly those for ribosomal proteins. Mutational disruption of G4s in ribosomal protein UTRs alleviates translation in vitro, whereas in cells, depletion of G4-resolving helicases or treatment with G4-stabilising small molecules inhibit the translation of ribosomal protein mRNAs. Our findings point to a common mode for translational co-regulation mediated by G4 structures. The results reveal a potential avenue for therapeutic intervention in diseases with dysregulated translation, such as cancer. Evidence from chemical biology and genetic experiments has accumulated in support of a role for RNA G4s in translational regulation of disparate mRNAs such as NRAS2, BCL23 and ADAM104 in vitro and in cells. Potential formation of RNA G4s in thousands of transcripts has been demonstrated in vitro using transcriptome-wide approaches, including reverse transcriptase (RT) stalling based rG4-seq5, and SHALiPE6 which detects differences in acylation kinetics of 2′-hydroxyl groups. Imaging experiments using a G4 structure-specific antibody, as well as application of small molecule stabilising ligands to cells, have provided significant evidence for the bona fide cellular existence of RNA G4s7. Experiments to chemically map RNA structure formation in cells by DMS and SHAPE have suggested that RNA G4s may be largely unfolded due to the activity of cellular proteins8. In contrast, a recent in-situ chemical mapping study using azido-kethoxal in combination with RT-stalling provided evidence for the formation of RNA G4s in cells9. The ability of such methods to detect G4 structures is somewhat limited as they can alter the equilibrium by chemically trapping dynamic structures in an unfolded state and therefore the reaction conditions need to be carefully optimised to sample dynamic or lowly populated structures (see10 for more extensive discussion).RNA G-quadruplexes (G4s) are thought to influence diverse aspects of biology that include transcription, splicing, sub-cellular localisation, translation and decay11. For example, the abundant DHX36 RNA helicase has sub-nanomolar affinity for RNA G4s12. Mechanistic studies show that DHX36 binds a folded G4 structure to unwind it in an ATP-independent manner, but can remain bound to facilitate G4 refolding in an ATP-dependent step-wise process14. Multiple rounds of folding and unfolding can occur prior to dissociation of the enzyme. This indicates that, RNA G4s, much like DNA G4s15, undergo dynamic interconversion by associated proteins. Many roles for G4s have been inferred in RNA biology, but critical information regarding their abundance, dynamics and locations within the cellular transcriptome is lacking. Herein, we present evidence for frequent G4 formation in the cellular transcriptome through experiments that exploit endogenous RNA binding proteins and also an engineered G4 structure-specific antibody. Our data reveal many G4s that have hitherto been unrecognised in the endogenous transcriptome and highlight a striking enrichment of G4s in a subset of mRNAs essential for ribosomal assembly. Through chemical biology interventions, we demonstrate a direct role for RNA G4s in the regulation of cellular ribosomal protein production and discuss their possible role in regulating global translation.The identification of numerous proteins that unwind G4s in RNA, suggests that cells have mechanisms to actively suppress these structures11. We previously used RNA crosslinking and affinity enrichment (termed iCLAE) to demonstrate that DDX3X binds RNA G4s in cells via its GAR domain11. To generate a more comprehensive cellular map of RNA G4s, we have generated additional data for DHX36 and GRSF1 using the same cell line (HEK293 Flp-In T-REx) and iCLAE methodology11. Briefly, expression of Streptactin/haemaglutinin (ST/HA)-tagged DHX36/GRSF1 was induced to reflect endogenous levels of protein expression  alongside the DHX36 and GRSF1 iCLAE data for consistency. We have previously described DDX3X iCLAE data in detail11, but briefly, 4557 consensus peaks from three independent replicates of DDX3X iCLAE (Pearson’s correlation > 0.74) showed significant enrichment in 5′ UTRs  of mRNA . Two-tetrad G4s comprise the majority (60%) of peaks, which is 2.9-fold greater than random (FDR < 1 × 10−4). Since two-tetrad motifs are more prevalent across the transcriptome when compared to three-tetrads, this results in a greater chance of being sampled at random and therefore a lower fold change.The RNA helicase DDX3X selectively binds the NRAS RNA G4 in vitro (Kd = 18 nM for NRAS RNA G4) with minimal binding to the mutated G4 Fig. a. Our exRNA Fig. b. Three −4) over previously published PAR-CLIP peaks for DHX36  of these peaks were found in 3226 protein coding mRNAs , whereas in 3′ UTRs an AU-rich motif was more prevalent  were found to overlap with G4 motifs  and a greater enrichment of rG4-seq verified G4s  when compared to random.In vitro, recombinant DHX36 demonstrates sub-nanomolar affinity for RNA G4s . ThreeX36 Fig. a16. The 119 Fig. a. Peaks 119 Fig. b16. Motiifs Fig. c, of whibona fide interactor of the RNA G4 from NRAS 5′ UTR11. GRSF1 has also been reported to specifically interact with RNA G4s in vitro, where binding is suggested to promote G4 unfolding17. A role for GRSF1 as a G4 surveillance factor that mediates the decay of mitochondrial non-coding RNAs has been suggested17. Four independent iCLAE replicates showed good signal correlation  map to nuclear chromosomes with 55% located in 4228 protein-coding mRNAs, strongly suggesting a non-mitochondrial role for GRSF1  and 3′ UTRs  for G4 motifs  than random.We previously identified GRSF1 as a 11. Therefore, our iCLAE data confirms that two-tetrad G4s form in the human transcriptome, in line with other in vitro23, and in vivo reports27. DDX3X, DHX36 and GRSF1 bind primarily to distinct target sites  and faithfully reflect the corresponding biophysical observations.Data from phase III of the Encode project indicates that the cellular RNA target sites for many RNA binding proteins are defined by their in vitro binding specificities7. BG4 shows high affinity for G4 structures (Kd ~ low nM) with little cross-reactivity to linear or non-G4 nucleic acid structures31. We first UV-crosslinked cells to trap RNA-protein complexes in their endogenous states, followed by limited RNA fragmentation using RNaseA and then finally BG4 affinity capture of folded G4 structures  RNA G4s previously identified in purified, protein-free transcripts by reverse transcriptase-stalling (rG4-seq) were in 3′ UTRs with enrichment near polyadenylation signals5, whereas in a cellular context BG4 uvRIP experiments revealed that only 7.5% of BG4 peaks are found in 3′ UTRs. A possible explanation for this is that G4s within 3′ UTRs are more often unfolded or bound by proteins that mask detection by BG4 as opposed to the G4s within 5′ UTRs. The proteins that recognise G4s within 5′ UTRs may also differ from the ones that bind G4s in 3′ UTRs and may therefore differently impact recognition by BG4.To provide cross-validation for the formation of RNA G4s in mRNAs by an orthogonal approach, we performed affinity enrichment experiments with the well-characterised G4-structure specific single chain antibody BG4res Fig. a. This cres Fig. . BG4 peares Fig. c,d. Our 2fold; FDR < 0.001; Fig. Confirming identification of G4 structures in RNA, BG4 peaks show statistical enrichment for G4 motifs  of such ‘BG4-confirmed’ RNA G4s within mRNA coding for ribosomal proteins, based on functional annotation analysis using DAVID (LHRI), where no other functional annotation term was found to be significantly enriched. On further scrutiny of our iCLAE data, we also found that majority of annotated ribosomal protein mRNA (61/82) contain a G4-motif within their 5′ UTR that is bound by one or more G4-binding proteins. Analysis of iCLAE sites common to all three G4-binding proteins assayed by us also showed a significant enrichment for ribosomal protein mRNAs .To gain insights into the biological role of RNA G4s, we focused on the 513 sites that were shown to interact with at least one of the G4 binding proteins DDX3X, DHX36 or GRSF1 in iCLAEs and also detected independently by BG4 uvRIP Fig. . Our att34 in which we identified G4 structures that show sequence conservation in higher vertebrates  and thermal melting37 assays. G4-containing oligonucleotides bound Thioflavin T and showed increased fluorescence when compared to mutated G4 oligos containing G to A mutations that disrupt G4 formation  motif which is followed by a G-rich stretchtes Fig. . The folion Fig. a. Ribosoion Fig. b with thays Fig. c. Typicaon Figs. c, S11. C−26) downregulated protein family16. Moreover, depletion of DDX3X in melanoma cells has been reported to inhibit the translation of ribosomal protein mRNAs and cause reduction in overall cellular translation38, however the involvement of G4s was not noted by the authors. These data show that G4-unwinding helicases regulate the expression of ribosomal proteins.Since G4s in ribosomal protein mRNA are bound by one or more G4-interacting proteins Fig. , we asse34 and we therefore reasoned that these common structural features may be involved in regulating translation and thereby control ribosome synthesis, which in turn would globally regulate translation. To specifically assess the influence of these G4s on translation, we adopted a cell-free translation system previously used for the study of NRAS 5′ UTR2. A selection of 5′ UTRs from ribosomal protein mRNA were cloned upstream of the firefly luciferase gene along with versions carrying mutations that disrupt G4 folding. Mutation of G4s led to a significant increase in translation for all ribosomal protein UTRs studied, confirming a role for these G4 structures in regulating translation of ribosomal proteins  and statistical significance were determined from three independent biological replicates . Strikingly, most ribosomal protein mRNA showed a decrease in translation upon PDS treatment  for a brief period of 45 min, which circumvents effects from transcriptional or DNA damage responses that are associated with longer treatmentstes Fig. . Supportnts Fig. a. To detnts Fig. . In agrents Fig. .5 and Keth-seq9 datasets reveals that these methods also detected the presence of G4s in ribosomal protein mRNA. Through chemical biology interventions we have discovered that stabilised G4s interfere with translation of ribosomal proteins, which also explains the reduced ribosomal protein synthesis that is seen following loss of RNA G4 resolving proteins such as DDX3X and DHX36. Through inspection of publicly available data, we found ribosomal protein mRNA are also targets of CNBP (cellular nuclear acid binding protein). CNBP has been suggested to bind G-rich regions to prevent G4 formation thus facilitating translation40. Our scrutiny of proteomics data following depletion of CNBP also reveals a reduction in ribosomal protein levels40. Together with observations in this study, this points to multiple G4-interacting proteins with a role in regulating ribosomal protein synthesis.Overall, we have uncovered a set of cellular RNA G4s based on their recognition by a G4-structure specific antibody and endogenous G4-interacting proteins. Our work specifically highlights G4s as a feature of ribosomal protein mRNA. Appraising rG4-seq41. Depletion of DDX3X and DHX36 has been reported to cause increased formation of stress granules42.It is unclear if these proteins can co-occupy the same individual transcript or whether they interact with distinct transcript sub-populations from the same gene. Another unresolved question is why the loss of individual G4 resolving proteins is not compensated by the activity of others that seem to engage the same target G4, including the ubiquitous helicase EIF4A? One possible explanation may be that the loss one of these proteins shifts the balance resulting in sequestration into sub-cellular compartments such as stress granules to modulate translation. Stress granules are cytoplasmic protein-RNA aggregates that form in response to cell stress and mRNA with more structured UTRs show greater propensity to localise to these bodies34. Our polysome profiling data with 2 µM PDS showed a small decrease of RNA in the polysomal fractions indicating an impact on global translation  stable cell lines expressing Strep-tag (ST)/HA affinity tagged GRSF1 and DHX36 were generated by transfection of pcDNA5/FRT/TO vector as per manufacturers protocol (ThermoFisher). Cells were selected with Blasticidin (Gibco) and Hygromycin D (Sigma). For shRNA knockdowns, SMARTvector inducible lentiviral shRNA system (Dharmacon) was used to generate viral particles. Transduction efficiency was optimised to 30% to ensure single incorporation events and hairpin expressing cells selected as per manufacturers’ instructions. Protein knockdowns were achieved by treating cells with 1 μg/ml Doxycycline for 72 h.® infrared spectrometer (Merck Millipore), equal amounts of lysate subjected to SDS PAGE and immunoblotting, and signal was visualised and quantified using Odyssey CLx and Image Studio (Licor) using the following antibodies actin  and γH2AX . WES (ProteinSimple) automated Western Blotter was used with antibodies against RPL12 , RPS12 , RPS19 , DHX36 ; DDX3X ; GRSF1  and actin .Cells were lysed in Pierce™ RIPA buffer (Thermo Fisher) as per manufacturer’s instructions. Protein lysates were quantified using Direct DetectELISA assays using recombinant proteins were performed as in Zyner et al.43, using the NRAS G4 oligo 5′-UGU GGG AGG GGC GGG UCU GGG UGC-3′ and NRAS mG4 oligo 5′-UGU AGA AAG AGC AGA UCU AGA UGC-3′. Purified recombinant DDX3X was obtained from OriGene Technologies (TP304171) and recombinant DHX36 was purified as described in Chen13.HindIII restriction site, and followed by 5′ section of the firefly luciferase gene and BstBI restriction site were ordered as gene blocks (ThermoFisher). Restriction digested gene blocks were used to replace the NRAS 5′ UTR in the pUC18 vector described in Kumari et al.2. G4 sequences were mutated by site directed mutagenesis. In vitro translations assays were performed as described in Kumari et al.2. Briefly, linearised plasmids were in vitro transcribed using the mMessage mMachineTM T7 transcription kit (ThermoFisher) as per manufacturers’ instructions. Resulting capped mRNA were gel purified with Zymoclean™ RNA gel recovery kit (Zymo Research). Equimolar amounts of UTRQ and mutQ RNA were in vitro translated using nuclease treated Rabbit Reticulocyte lysates (Promega) as per manufacturers’ instructions. Luciferase activity was determined with Steady-Glo® Luciferase assay system (Promega) and luminescence measure with a CLARIOstar microplate reader (BMG Labtech).5′ UTRs from ribosomal protein mRNA preceded by a minimal T7 promoter and a iCLAE experiments were performed as in Herdy et al.11. Briefly, protein expression was induced using 0.01 μg/ml Doxycycline overnight. Cells were UV-crosslinked  and cytoplasmic lysates collected by hypotonic lysis. Lysates were adjusted to a final concentration of 50 mM Tris–HCl (pH 7.4) 100 mM NaCl and 0.1% SDS, and subjected to limited RNase digestion for 3 min at 37 °C. Lysates were subjected to affinity enrichment and iCLAE library prep as described in Herdy et al.11 and Huppertz et al.29. Reverse transcription was performed with SuperScript III using G4 optimised lithium buffers as in Kwok et al.5.44. Crosslinked cytoplasmic lysates were generated using hypotonic lysis as for iCLAEs. RNA concentration was quantified using Qubit broad range RNA assay kits. For each biological replicate, seven 1.5 ml tubes containing 43 μl of blocking buffer  BSA) and 2.5 μl of lysates measuring 400–600 ng/μl RNA were prepared on ice. All aliquots were digested with 2U Turbo™ DNase (Thermo Fisher) at 37 °C for 5 min and cooled on ice. Limited RNaseA digestion was performed at 37 °C for 3 min, aliquots rapidly cooled on ice and 1 μl RNasin® (Promega) added to each aliquot. The remainder of the protocol was performed on ice.The protocol was adapted from G4 ChIP as in Hansel-Hertsch et al.2.5 μl Flag-tagged BG4 antibody (4 μM) or 2.5 μl A9 antibody (μM) were added to three aliquots each and 2.5 μl PBS was added to one aliquot that was used as Input and left at 4 °C until the proteinase K digestion step. All aliquots were incubated at 4 °C for 60 min. Anti-FLAG M2 magnetic beads  were washed three times with block buffer and resuspended in 650 μl block buffer. 50 μl beads were added to each BG4 and A9 IP aliquots, and all aliquots incubated at 4 °C for a further 60 min. The BG4 and A9 IPs were then washed with 200 μl wash buffer  four times at 4 °C and twice for 10 min shaking at 37 °C. The IP aliquots were resuspended in 150 μl PK-SDS buffer  and pooled into one BG4 and A9 sample respectively. 5 μl of the Input was added to 445 μl PK-SDS buffer to give a 10% Input. Samples were de-crosslinked and de-proteinated by addition 10 μl Proteinase K  and incubation at 50 °C for 60 min. RNA was purified using Phenol/Chloroform/isoamyl alcohol, phase separated by Heavy Phase lock tubes (QuantaBio) and precipitated overnight at − 20 °C with 1.5-fold volume of isopropanol, 150 mM sodium acetate pH 5.5 and 1 μl GlycoBlue™ (Thermo Fisher). Samples were centrifuged for 30 min at 4 °C and RNA pellet resuspended in 15 μl water.® rRNA depletion kit (New England Biolabs) as per manufacturer’s instructions with one alteration that allows for purification of small RNA fragments. Ribodepleted RNA was not purified with NEBNext® RNA sample purification beads as described by the manufacturer but with phenol chloroform purification as described above. Libraries were then prepared using NEBNext® Ultra™ II Directional RNA Library Prep Kit (New England Biolabs) as per manufacturer’s protocol with the following alterations. Quadruplex optimised reverse transcription buffer5 was used for first strand synthesis instead of manufacturer supplied buffer. Following second strand synthesis, cDNA was purified using Qiaquick® nucleotide removal kit (Qiagen) instead of using SPRISelect beads (Beckman Coulter™).RNA subjected to Ribodepletion with NEBNexthttps://github.com/sblab-bioinformatics/rna-g4-proteins. The previously published DDX3X libraries were reprocessed using this approach for consistency. Briefly, libraries were demultiplexed, filtered based on quality, duplicates removed and aligned to the human reference genome  using bwa allowing for 0.06 err rate45.iCLAE and BG4 uvRIP sequencing data were processed and peaks were called as described in 46 using a p-value cutoff of 0.0001 and consensus peaks defined as peaks occurring in two or more biological replicates. For BG4 uvRIP, all regions of read density above 1 count per million in the BG4 and A9 libraries were identified and reads aligned within these regions counted for all input and IP libraries. Peaks were defined as regions of differential enrichment compared to input (log2FC > 0.8 and FDR < 0.05) using differential binding analysis in EdgeR47. Overlaps and enrichments over genomic features and G4 motifs were obtained using bedtools48 and the genomic association tester (GAT49). Functional annotation analysis was performed using DAVID (LHRI) and GSEA (Broad Institute). Tracks shown in the manuscript comprise BigWig files generated by aggregation of individual biological replicates. Where indicated BG4 uvRIP tracks show BigWig files generated by calculating the log2FC between cumulative BG4 or A9 tracks to the cumulative input track.For iCLAE, aligned reads were further deduplicated using unique barcode identifiers within the adapters. Peaks were called using Piranha50. Briefly, cells treated for 45 min with indicated concentration of PDS or DMSO were incubated with cycloheximide, lysed and polysome fractions collected. Total RNA and RNA from polysomal fractions was isolated using TRIzol® (Life Technologies) as per manufacturer’s instructions. Library preparation was performed using the TrueSeq RNA library prep kit (Illumina). Translational efficiency was calculated as the ratio of counts per million in polysome fractions to counts per million in total lysate. Detailed data analysis pipeline was as described on https://github.com/sblab-bioinformatics/rna-g4-proteins.Polysome profiles were prepared as previously described35. CD spectra were obtained on an Applied Photophysics Chirascan Plus circular dichroism spectropolarimeter.RNA oligonucleotides purchased from IDT were diluted to 10 μM in 10 mM Lithium cacodylate buffer (pH 7.4) with 150 mM LiCl or KCl and were folded by heating at 95 °C for 5 min and slow cooling to 4 °C at the rate of 0.5 °C/min. Thioflavin-T binding assay was performed as described in Xu et al.Cells were treated with 2 μM PDS for two hours and harvested in ice cold PBS containing protease and phosphatase inhibitors (Roche). Cell pellets resuspended in lysis buffer containing 100 mM Triethylammonium bicarbonate , 0.1% SDS were heated at 90 °C for 5 min and sonicated. Protein concentration was estimated using Bradford assay (BIO-RAD-Quick start). 90 μg of total protein were reduced with 2 μl of 50mM tris-2-caraboxymethyl phosphine  for 1 h at 60 °C followed by alkylation with 1 ul of 200mM methyl methanethiosulfonate  for 10 min at room temperature (RT). Then protein samples were digested overnight at 37 °C using trypsin solution at ratio protein/trypsin ~ 1:30. The next day, protein digest was labelled with the TMT-10plex reagents (Thermo Scientific) for 1 h. The reaction was quenched with 8 μl of 5% hydroxylamine (Thermo Scientific) at room temperature for 15 min. All the samples were mixed and dried with speed vac concentrator. The dry TMT mix was fractionated on a Dionex Ultimate 3000 system at high pH using the X-Bridge C18 column  with 90 min linear gradient from 5 to 95% acetonitrile contained 20 mM ammonium hydroxide at a flow rate of 0.2 ml/min. Peptides fractions were collected between 20 and 55 min and were dried with speed vac concentrator. Each fraction was reconstituted in 0.1% formic acid for liquid chromatography tandem mass spectrometry (LC–MS/MS) analysis.51. Briefly, peptide fractions were analysed on a Dionex Ultimate 3000 system coupled with the nano-ESI source Fusion Lumos Orbitrap Mass Spectrometer (Thermo Scientific). Peptides were trapped on a 100 μm ID × 2 cm microcapillary C18 column  followed by 2 h elution using 75 μm ID × 25 cm C18 RP column  at 300 nl/min flow rate. In each data collection cycle, one full MS scan (380–1500 m/z) was acquired in the Orbitrap  setting of 3 × 105 and Maximum Injection Time (MIT) of 100 ms). The subsequent MS2 was conducted with a top speed approach using a 3-s duration. The most abundant ions were selected for fragmentation by collision-induced dissociation (CID). CID was performed with a collision energy of 35%, an AGC setting of 1 × 104, an isolation window of 0.7 Da, a MIT of 35 ms. Previously analysed precursor ions were dynamically excluded for 45 s. During the MS3 analyses for TMT quantification, precursor ion selection was based on the previous MS2 scan and isolated using a 2.0 Da m/z window. MS2–MS3 was conducted using sequential precursor selection (SPS) methodology with the top10 settings. HCD was used for the MS3, it was performed using 55% collision energy and reporter ions were detected using the Orbitrap .LC-MS/MS was performed as in Papachristou et al.https://github.com/sblab-bioinformatics/rna-g4-proteins.The Proteome Discoverer 2.1. (Thermo Scientific) was used for the processing of CID tandem mass spectra. The SequestHT search engine was used and all the spectra searched against the Uniprot Homo sapiens FASTA database (taxon ID 9606—Version February 2017). All searches were performed using as a static modification TMT6plex (+ 229.163 Da) at any N-terminus and lysines and Methylthio at Cysteines (+ 45.988 Da). Methionine oxidation (+ 15.9949 Da) and Deamidation on Asparagine and Glutamine (+ 0.984) were included as dynamic modifications. Mass spectra were searched using precursor ion tolerance 20 ppm and fragment ion tolerance 0.5 Da. For peptide confidence, 1% FDR was applied and peptides uniquely matched to a protein were used for quantification. Differential analysis was performed as described on Supplementary Information 1.Supplementary Information 2.Supplementary Information 3.