UK's National Health Service (NHS) has been increasingly endorsed. However, there is very little research on whether – and how – this is enacted in practice. Based on 223 recordings of neurology outpatient consultations and participants’ subsequent self‐reports, this article shows that ‘option‐listing’ is a key practice for generating the perception of choice. The evidence is two‐fold: first, we show that neurologists and patients overwhelmingly reported that choice was offered in those consultations where option‐listing was used; second, we demonstrate how option‐listing can be seen, in the interaction itself, to create a moment of choice for the patient. Surprisingly, however, we found that even when the patient resisted making the choice or the neurologist adapted the practice of option‐listing in ways that sought acceptance of the neurologist's own recommendation, participants still agreed that a choice had been offered. There was only one exception: despite the use of option‐listing, the patient reported having no choice, whereas the neurologist reported having offered a choice. We explore this deviant case in order to shed light on the limits of option‐listing as a mechanism for generating the perception of choice.The normative view that patients should be offered more choice both within and beyond the  Choice Matters, lays out a broad vision for the implementation of patient choice within the NHS, and specifies forms of choice to be made available  within a target timescale. Patient choice in the UK's NHS is, then, both carefully delimited and articulated as a broad aspiration.The view that patients should be offered more choice within publicly‐funded healthcare settings has been increasingly endorsed over the last two decades Dent . Indeed,et al.  easy to pin down, the enactment of choice – during face‐to‐face decision‐making – is far from self‐evident. The few studies that have investigated choice in interaction have shown significant discrepancies between policy and practice. Pilnick  notes thet al.  similarlet al. et al.  on 11 October 2011.et al. Our primary approach was conversation analysis (CA). CA is a micro‐analytic, systematic methodology, widely recognised as the leading approach for investigating how doctor‐patient interaction functions  of cases for which we have the relevant questionnaire data, the neurologist reported offering the patient a choice, and in 71.8 per cent (145/202) of cases for which we have the data, the patient reported being offered a choice. Table 46/215 ofet al.  for a stOur qualitative analysis revealed a striking finding: with just one exception , and sometimes embedded within an interrogative (e.g. ‘would you like to x … would you like to y … would you like to z …’), some of which were either/or choices. Doing nothing was sometimes included explicitly. Component 3 entails inviting the patient to announce their views on the options and/or to select one. We refer to this component as a patient view elicitor (PVE), encompassing turns that ask what the patient wants, how they feel, and what they think about the options.As demonstrated previously (Reuber http://www.paultenhave.nl/Transcription-DCA-2.htm. The identifiers show where the consultation was recorded (Glasgow or Sheffield), the number of the recording (numbered consecutively at each site from 001), followed by a two‐digit number for each clinician.The three‐component package is illustrated in Extract 1 (see boldface across lines 1–116). Having already advised changing one of the patient's anti‐epileptic drugs, the neurologist sets up a decision regarding what to take instead. At lines 1–2 he projects a forthcoming list (component 1). At lines 7, 40 and 72, he names three options (component 2). At lines 115–116, he invites the patient's view on the options (component 3), which the patient provides . For a key to the transcription conventions used in CA, please see: Extract 1et al. et al. The components combine to offer the patient an explicit choice. In component 1, the neurologist names the information to come as a listing of ‘possibilities’ rather than a recommendation. In clearing space to ‘talk through these’ (line 2), he signals that the information is to be understood as part of a deliberation process  that neurologists and patients almost always agreed that a choice had been offered following consultations in which option‐listing was used. Crucially, however, patients did not always take up this opportunity to choose. Extract 2 provides a contrast to Extract 1. Both patients are young men, accompanied by their parents. Both have epilepsy and are offered – by the same neurologist – a choice of anti‐epileptic drugs as a replacement for one that has not been working well. In both, the neurologist uses option‐listing in a similar way, announcing a choice to be made, listing more than one option, and seeking the patient's views on/selection from the list. Extract 2 shows this final component (boldfaced lines 108 and 110) and the responses produced by patient and parents.Extract 2The contrast in responses to the option‐listing shown in Extracts 1 and 2 is marked. In 1, the patient takes up the opportunity to choose. Across lines 117–118, 151–152, and 180, we see him mirroring the neurologist's list by considering each option himself, finally concluding that the first is the one to try (line 180). This decision‐making is clearly guided by the neurologist, as he humorously recognises . Indeed, the patient's selection is built as a logical conclusion of the line of reasoning that has occurred, rather than simply as his personal preference: ‘so really it's the first one …’ (line 180). Nevertheless, it is the patient who articulates that conclusion, treating it as based on his evaluation of the evidence, his concerns about potential side effects, and the risks of trying a new drug.et al. By contrast, in Extract 2, the patient has difficulty in responding, evident in the silence at lines 109 and 111, and breathy laughter at 112. Subsequently, his mother asks a question (lines 116–122) and his father seeks the neurologist's view (lines 135–136). This results in a recommendation, which the family accepts, thus making this a matter of ‘assent’, rather than an expression of an independent ‘choice’ Pilnick, . NeverthThese contrasting cases demonstrate – in practice – the distinction between having a choice and making one. Following both consultations, patient and neurologist reported that a choice had been offered. Our data indicate, then, that option‐listing does not lose its capacity to generate the perception of choice even if the neurologist makes the decision.et al. Extract 3 shows how option‐listing can be adapted , several more overtly aligning acknowledgements , and some possible indicators of accepting the recommendation . Moreover, he makes no overt recommendation prior to the option‐listing. Extracts 4a–b, by contrast, show a decision sequence that begins with a recommendation (see boldfaced lines 1 and 7–11), acceptance of which the neurologist pursues repeatedly, before using option‐listing . In the absence of a fitted response to his recommendation (which could have occurred at line 12), the neurologist seeks the patient's view . Her response remains rooted in how often she experiences her ‘turns’ (lines 14–16 and 19). This misalignment continues in a manner that could be understood as resistance to monitoring (data not shown). What matters, for our purposes, is that the neurologist employs option‐listing only after he has failed to secure the patient's acceptance of his recommendation.We rejoin the interaction at a point where the neurologist is trying (again) to gain this acceptance . He looks set to reissue his recommendation  but instead provides a justification, strongly positioning the recommended investigation as a necessary precursor to treatment (lines 57–63). He then employs a condensed but clear version of option‐listing . At lines 65–66, he flags up that there is a decision to be made, placing this in the patient's domain: ‘you need to decide what you would like us to do’ (component 1). He then lists two options, formatted as an interrogative (lines 66–70), thereby folding the action of listing (component 2) and seeking the patient's view (component 3) into one unit.Extract 4bThe design of the options is clearly not neutral. In constructing the option of monitoring, the neurologist not only upgrades its utility (line 68), but makes treatment contingent on this investigation (lines 68–69). Moreover, the alternative is set up as unsatisfactory for the patient: having to ‘soldier on’ entails coping in the face of adversity, which could be lessened if they identified an appropriate treatment. Moreover, this amounts to ‘doing nothing’, which could be argued to construct little choice. The terms of the decision are set, then, to make it difficult to bid for no monitoring. Although the neurologist has used the machinery of option‐listing, he has done so in a way that constructs another version of his recommendation, pursuing acceptance thereof.Mum addresses the second option as if it were a single yes/no question,Comparing Extracts 1 and 4a–b, we see the malleability of option‐listing. Although both produce a list from which the patient may choose, the neurologist in 1 constructs viable alternatives, whereas the neurologist in 4b uses option‐listing to pursue acceptance of his recommended option. Nevertheless, in their post‐consultation questionnaires, participants in both reported that a choice had been offered.et al. Extract 5 shows a deviant case in that the neurologist reported that a choice had been offered, and the patient that it had not. The patient has long‐standing epilepsy, which is not fully controlled. The neurologist has concluded that they should reduce one of her drugs because it appears to be causing fatigue and not improving seizure control. The question is what else they might try. The neurologist makes a bad news announcement: they have, more or less, run out of alternatives and ‘the chances of getting [her] seizure free are really very low indeed’. Implicitly, he is recommending continuing with her current medication. In this regard, his turn is comparable to cases in our no‐choice subset . Again, we see the familiar three components. He flags up that a decision is to be made (line 15), lists two alternatives (lines 15–16 and 18–22), places the decision in the patient's domain (lines 15 and 23–24), and uses a PVE to hand the decision to the patient (lines 38–39). When this fails to elicit a response (line 40), the neurologist returns to his original position: that he has little to offer.Extract 5within the consultation. The neurologist frames the decision as the patient's ‘choice’ (line 99), but the patient and her husband construct it starkly as a non‐choice, using the imperatives: ‘gotta live with [it]’ (lines 103–104) and ‘need to stick with the situation’ (line 109). The use of option‐listing – and even the phrase, ‘it's your choice’ – does not, then, guarantee that patients will experience themselves as having genuine alternative options.The disagreement in the neurologist's and patient's self‐report data is evident et al. However, this was the only case  where option‐listing was used to generate a decision about a test, treatment or referral that was not perceived by the patient as offering choice. What distinguishes this from the rest? Its unique feature lies in what it lacks: the construction of any option as likely to address the patient's trouble. Choice is there in the formal sense: the patient is, as the neurologist reports, given the option to try an alternative drug. However, choice is not there, as the patient reports, in a substantive sense: no option is presented as likely to make any difference  choice.et al. et al. Previous research has shown that patients report concern about choice performed as ‘a politically driven box‐ticking exercise’  an expert opinion of what is best’ , then option‐listing may sometimes operate less as a practice for reducing authority and more as one for disguising its exercise. Although there can be good reasons for persuading patients to do things they would rather not, such practices sit uncomfortably alongside the widespread endorsement of a more egalitarian relationship between doctors and patients. Simply advocating the use of option‐listing carries no guarantee that it will produce a genuine moment of choice for the patient in practice.However, and this is the third reason for caution, it may be that the policy directive to increase ‘patient choice’ is a red herring. There is now a vast body of literature advocating a multi‐faceted model of ‘shared decision‐making’ (SDM), which allows for significant patient involvement but also pushes back against a consumerist model, in which the patient is left to choose as if making a purely preference‐based decision, like whether to order coffee or tea. SDM emphasises interactional approaches that facilitate informed decision‐making, which balances the patient's preferences and the current state of medical evidence (e.g. Elwyn and Edwards To our knowledge, ours was the first study to focus on what constitutes, specifically, ‘patient choice’ from the dual perspective of participants’ self‐reports and close analysis of real decision‐making. Further research is needed to address the limitations of our study, which include the possibility that our findings could be specific to neurology, to secondary care, to NHS practice, and/or to chronic disorders. Future research might also seek more nuanced accounts of participants’ perceptions of choice using interviews instead of brief questionnaires.This article has focused on the only practice for giving patients choice that we identified as characteristic of those consultations in which participants agreed that a choice had been offered. However, option‐listing was not the only practice used to initiate decision‐making in this subset. Moreover, in roughly a third of our consultations neurologists and patients disagreed about whether choice had been offered. It is clear, then, that what constitutes patient choice is far from self‐evident. Given the extent to which NHS policy encourages clinicians to offer patients more choice, unpicking what this means in practice should be a priority.


By comparing various pentanucleotide repeats in this particular locus among control Japanese and Caucasian populations, it was found that (TGGAA)n was the only sequence segregating with SCA31, strongly suggesting the pathogenicity of (TGGAA)n. The complex repeat also lies in an intron of another gene, TK2 (thymidine kinase 2), which is transcribed in the opposite direction, indicating that the complex repeat is bi-directionally transcribed as noncoding repeats. In SCA31 human brains, (UGGAA)n, the BEAN1 transcript of SCA31 mutation was found to form abnormal RNA structures called RNA foci in cerebellar Purkinje cell nuclei. Subsequent RNA pulldown analysis disclosed that (UGGAA)n binds to RNA-binding proteins TDP-43, FUS, and hnRNP A2/B1. In fact, TDP-43 was found to co-localize with RNA foci in human SCA31 Purkinje cells. To dissect the pathogenesis of (UGGAA)n in SCA31, we generated transgenic fly models of SCA31 by overexpressing SCA31 complex pentanucleotide repeats in Drosophila. We found that the toxicity of (UGGAA)n is length- and expression level–dependent, and it was dampened by co-expressing TDP-43, FUS, and hnRNP A2/B1. Further investigation revealed that TDP-43 ameliorates (UGGAA)n toxicity by directly fixing the abnormal structure of (UGGAA)n. This led us to propose that TDP-43 acts as an RNA chaperone against toxic (UGGAA)n. Further research on the role of RNA-binding proteins as RNA chaperones may provide a novel therapeutic strategy for SCA31.Spinocerebellar ataxia type 31 (SCA31) is one of the autosomal-dominant neurodegenerative disorders that shows progressive cerebellar ataxia as a cardinal symptom. This disease is caused by a 2.5- to 3.8-kb-long complex pentanucleotide repeat containing (TGGAA) PLEKHG4  that encodes a protein with a spectrin repeat and Rho guanine-nucleotide exchange-factor domain [PLEKHG4, and the other border at rs11640843 with a recombination among affected individuals demonstrating a new 900-kb critical region [Spinocerebellar ataxia type 31 (SCA31) is one of a group of disorders that shows progressive cerebellar ataxia as a cardinal symptom with an autosomal dominant inheritance. This disease was first described when one of us (KI) and his colleagues found their families are mapped to a long arm of chromosome 16 , follower domain , indicatr domain . In suppr domain . Fortunal region .n, (TAGAA)n, (TAAAA)n, and (TAAAATAGAA)n n, (TAGAA)n, and (TAAAATAGAA)n. The (TGGAA)n was never observed in controls. In addition, presence of TGGAA repeat in SCA31 patients was also replicated in other researchers on different sets of patients [n was the only repeat segregating with the phenotype, suggesting its importance in pathogenesis.By a tiling search of small rearrangement by Northern blot analysis in conjunction with tiling-path shotgun sequencing of the newly set critical SCA31 chromosomal region in 16q22.1, a mutation shared by all family members with founder chromosomes was found to be a 2.5- to 3.8-kb-long insertion [patients . From thBEAN1  and TK2 (thymidine kinase 2). However, extensive 3′-RACE experiments revealed that these 2 genes both had multiple downstream exons that had not been deposited in the public databases. This means that the 2.5- to 3.8-kb-long insertion is in an intronic region shared by 2 different genes, BEAN1 and TK2 [BEAN1 drives brain-specific expression, TK2 was expressed in all tissues that we examined. As predicted, the TGGAA repeat was transcribed as UGGAA repeat in SCA31 brains.The insertion initially appeared to be unrelated to nearby genes, Identification of SCA31 repeat clarified clinical picture of SCA31. Typical clinical features can be found in some case reports and cohort studies –12. Sakan was never found in the Caucasian SCA families (n = 320) in French and German cohorts nor in the 588 healthy control subjects [n. Other repeats such as (GAAAA)n, (TGAAA)n, and (TAACA)n were also seen. Unlike the SCA31 insertion consisted of 3 different repeats (TGGAA)n, (TAGAA)n, and (TAAAA)n, the repeats found in Caucasians were all pure stretches. The most common (TACAA)n sometimes showed expansion up to 6.5 kb without clinical manifestation.As described, the SCA31 shows a strong founder effect. Although SCA31 is a common ataxia in Japan, this disease is very rare even in neighboring countries such as Korea , Taiwan subjects . Interesn in Japanese controls. However, all the expanded sequences in Caucasians were all single-nucleotide mutant versions of TAAAA. For example, (TACAA)n is a single A-to-C transition form. Such a mutation may make the SCA31 locus unstable. Second, the TGGAA repeat is the only sequence so far that leads to human disease. Considering that the TAGAA give rise to TGGAA by a single-nucleotide A-to-G transition, it seems likely that the TGGAA repeat, hence SCA31, originates from the TAGAA repeat which has been seen only in Japanese so far.This observation indicates 2 things. First, the SCA31 locus in which the vast majority of human beings harbors a short TAAAA repeat (8–20 repeats) can be expanded. The TAAAA can become unstable and expanded as we encountered long (TAAAA)28k, a useful Purkinje cell marker, revealed sprouts form the Purkinje cell body n as BEAN1 transcripts has been implicated as an important factor of SCA31 pathogenesis. To gain further insight into the SCA31 pathogenesis, in situ hybridization using RNA probes against (UGGAA)n or (UAGAAUAAAA)n was performed. Yusuke Niimi and his colleagues identified RNA foci within SCA31 Purkinje cells’ nuclei labeled positive with a locked nucleic acid (LNA)-oligonucleotide (TTCCA)5 probe [n [n is toxic than (UAGAAUAAAA)n in cultured cells. They created transient and stable expression cell systems and found that cell toxicity and formation of RNA foci were both consistently observed upon the expression of (UGGAA)n. These observations led us to conclude that (UGGAA)n could be toxic in cells.From the genetic observation, the (TGGAA))5 probe  Fig. 3)n transcrprobe [n . They alDrosophila models of SCA31 to express an expanded (UGGAA)n repeat RNA [Drosophila provides a rapid and powerful tool to model human neurodegenerative diseases [Drosophila models of SCA8 expressing (CUG)n repeat RNAs have been successfully established [n repeat followed by complex repeats consisting of (TAGAA)n, (TAAAA)n, and (TAAAATAGAA)n, from SCA31 patients, and established transgenic flies expressing expanded (UGGAA)n repeats (UGGAAexp) RNA under the UAS/GAL4 system. We also designed control transgenic flies carrying complex (TAGAA)n, (TAAAA)n, and (TAAAATAGAA)n repeats that are found in the normal Japanese population.To elucidate the molecular pathomechanisms of SCA31, establishing animal models is indispensable. We first tried to establish peat RNA , becausediseases , and Droablished . We firsGMR-GAL4 driver, we found that UGGAAexp (80–100 repeats) RNA caused remarkable eye degeneration depending on its expression level, whereas control repeat and short UGGAA22 RNA, which happened to be generated by spontaneous contraction of the TGGAA repeats, had no significant effect  revealed extensive accumulation of UGGAAexp RNA as RNA foci in eye imaginal discs of UGGAAexp-expressing flies  were identified as UGGAA-binding proteins, such as TDP-43 , FUS, and hnRNPs. After confirming TDP-43 in the (UGGAA)n-bound protein fraction, we further confirmed co-localization of TDP-43 with RNA foci in human SCA31 Purkinje cells, and thus decided to focus on TDP-43 to analyze its role in the SCA31 pathology [Considering that proteins sequestered in RNA foci have been reported to play an important role in the pathogenesis of noncoding repeat expansion disorders , Sato N.athology .exp-mediated toxicity, we crossed flies expressing UGGAAexp with those expressing human TDP-43. Surprisingly, co-expression of TDP-43 strikingly suppressed compound eye degeneration in the UGGAAexp-expressing flies  and atomic force microscopy (AFM) analyses were done by our colleagues led by C.E. Pearson demonstrated that the binding of TDP-43 to UGGAA repeat RNA alters its structure and prevents its aggregation, indicating that TDP-43 functions as an RNA chaperone for UGGAA repeat RNA [exp-expressing flies n-binding peptide may dampen its toxicity, which may further lead to a development of SCA31 therapeutics. Finally, disturbance of RNA-RBP cross-talk may not be the only possible mechanism of SCA31 pathogenesis. Further studies would be needed to discover mechanisms that (TGGAA)n leads to Purkinje cell predominant neurodegeneration.Currently, there is no fundamental treatment for SCA31. Therefore, RBP may provide a new idea for SCA31 therapeutics. Toward further elucidating the pathomechanisms of SCA31 and developing its potential therapies, we are now developing mouse models of SCA31. If we indeed see RNA foci containing (UGGAA)


OBJECTIVES/SPECIFIC AIMS: Endogenous RT (eRT) is necessary for the function of retrotransposons, elements that replicate via an RNA intermediate. One source of eRT activity is long interspersed elements (LINE). LINEs, of which there are several subgroups , are retrotransposons that regulate cellular growth and gene expression. Given their diverse and important roles, we hypothesized that L1 elements regulate functional responses in megakaryocytes and platelets; a concept not yet examined in the field. METHODS/STUDY POPULATION: To study eRT in human platelets we used RT activity assays, PCR, and Western blot approaches. Furthermore, we used an RT-inhibitor to dissect the function of eRT, analyzed RT-dependent protein synthetic capacity, and immunoprecipitated RNA-DNA hybrids. RNA-DNA hybrids were also detected by means of ICC and automated analysis using CellProfiler software. RNA-DNA hybrids were validated by PCR and eRT regulated synthesis of target proteins was analyzed using autoradiography and Western blot techniques. Platelets from patients with HIV+ were examined in parallel. RESULTS/ANTICIPATED RESULTS: We identified that highly purified, isolated platelets from healthy subjects possess eRT activity. eRT activity was blocked with the non-nucleoside RT inhibitor nevirapine at concentrations within the therapeutic drug range. L1 elements are bicistronic, containing 2 open reading frames (ORFs), ORF1 and ORF2. Thus, we next identified that human platelets express full-length L1 mRNA containing ORF1 and ORF2. In human platelets, eRT activity was localized to L1 protein containing ribonucleo particles. Platelet eRT reverse transcribed exogenous RNAs, a process inhibited by nevirapine, acting in trans using the 3′-UTR of exogenous mRNAs as a template. To dissect the function of eRT in platelets, we next examined cytoskeletal and protein synthetic events in the presence or absence of nevirapine. Inhibition of eRT in isolated platelets led to characteristically beaded platelets in appearance, strongly resembling bone marrow proplatelets. Parallel increases in platelet reactivity were also observed. As these changes occurred over hours, not minutes, we hypothesized that inhibition of eRT would affect platelet protein synthetic events. Consistent with this, RT inhibition resulted in upregulation of global platelet protein synthesis. We validated upregulation of the synthesis of specific proteins . RNA-DNA hybrids, noncanonical nucleic acid structures that regulate gene expression, are enriched in regions where L1 is abundant. RNA-DNA hybrids were present in platelets and expression confirmed via differential digestion of RNAs . Next-generation sequencing of pulled down  platelet RNA-DNA hybrids identified numerous differentially expressed transcripts and we focused on MAP1LC3B (LC3B), a primary regulator of autophagy. Hybrid sequencing results for LC3B were validated using qPCR and we confirmed that LC3B RNA binds to L1-encoded RNA binding protein. Platelets treated with nevirapine had increased total LC3B protein expression. As RT inhibition is an important mechanism to control HIV infection, we examined platelet morphology, activation, and LC3B expression in platelets from HIV+ subjects treated with nevirapine. HIV+ patients treated with RT inhibitors had higher numbers of platelets that were beaded in appearance at baseline, increased platelet reactivity, and differential LC3B expression compared with healthy controls. DISCUSSION/SIGNIFICANCE OF IMPACT: Taken together, these results demonstrate that platelets possess eRT activity that regulates platelet morphology, platelet hyperreactivity, and protein synthetic events. We postulate that eRT activity in platelets may be a new post-transcriptional regulatory checkpoint. Moreover, our findings have implications in HIV+ patients treated with RT inhibitors, where off-target effects may contribute to platelet activation and an increased risk of thrombosis.


Ribosomal RNA (rRNA) undergoes post-transcriptional modification of over 200 nucleotides, predominantly 2′-O-methylation (2′-O-Me). 2′-O-Methylation protects RNA from hydrolysis and modifies RNA strand flexibility but does not contribute to Watson-Crick base pairing. The contribution of 2′-O-Me to the translational capacity of ribosomes has been established. Yet, how 2′-O-Me participates in ribosome biogenesis and ribosome functioning remains unclear. The development of 2′-O-Me quantitative mapping methods has contributed to the demonstration that these modifications are not constitutive but rather provide heterogeneity to the ribosomal population. Moreover, recent advances in ribosome structure analysis and in vitro translation assays have proven, for the first time, that 2′-O-Me contributes to regulating protein synthesis. This review highlights the recent data exploring the impact of 2′-O-Me on ribosome structure and function, and the emerging idea that the rRNA epitranscriptome is involved in translational control. RNAs are no exception and modifications are found in all classes of RNA and in all living organisms. To date, at least 171 types of modifications have been identified  ,3,4. DecKre33, and substrate specificity guided by snoRNAs snR4 and snR45 [2′-O-Methylation is added to rRNA post-transcriptionally by ribonucleoprotein (snoRNP) complexes containing C/D box family small nucleolar RNAs (snoRNAs), thus termed C/D snoRNP complexes, in which the snoRNA defines the nucleotide to be methylated by sequence complementarity with rRNA . snoRNA-nd snR45 . The assnd snR45 ,8,9. In nd snR45 ,11,12. Tnd snR45 ,14,15.In humans, C/D box snoRNAs (or SNORD) are 70–120 nucleotides (nt) long and are mainly encoded within introns of coding genes, and processed from lariat introns upon mRNA splicing. Since many snoRNAs are encoded by genes associated with ribosomal biology, such as ribosome biogenesis factors or ribosomal proteins, it is expected that this genomic organization promotes co-regulatory mechanisms, although this remains to be demonstrated. C/D box snoRNP particles are assembled via a multi-step process, involving chaperone and helicase activities carried out by complexes such as R2TP ,17,18,19Evaluating the timing of 2′-O-Me has been a long-standing issue. Early studies demonstrated that 2′-O-Me is a nuclear event . More reRPL7A gene in humans). How such SNORD combinations contribute to regulating 2′-O-Me remains obscure.In most cases, a 2′-O-Me position is modified by a unique C/D box snoRNA so that single SNORD/2′-O-Me associations can be defined. However, there are a few cases of combinatorial associations, such as C/D snoRNAs modifying several sites  or 2′-O-Me positions modified by more than one C/D snoRNA  and ribosomal proteins. 2′-O-Me is one of the RNA modifications that does not directly alter the Watson-Crick laws governing base pairing, making its contribution to RNA structure and function even more complex to anticipate. In addition to protecting RNA from hydrolytic cleavage, a well-known consequence of 2′-O-Me is the stabilization of the nucleotide conformation , which is favored in RNA strands due to the OH group . In addiThere are no published follow-up studies focusing on the role of 2′-O-Me on RNA conformation, such as single strand rRNA or rRNA:protein complexes, that are found within ribosomes, and the field has thus not been updated for several years. Fortunately, recent progress in structural analysis of entire ribosomes has enabled the visualization of some rRNA modifications and unraveled their involvement in molecular interactions. Steitz’s laboratory reported a crystal structure of bacterial ribosome at a 2.3–2.5 Å resolution revealing several rRNA modifications including 2′-O-Me, and showed that they establish contact with ribosome ligands between the ribosomal subunits and within rRNAs . For exaThe role of 2′-O-Me on ribosome functioning and mRNA translation was initially explored in yeast in a series of studies in which both 2′-O-Me and ψ were selectively removed from key regions of the ribosome, such as the subunit interface, the peptidyl-transferase center, and the decoding center by introducing mutations into the corresponding snoRNA guide ,63,64,65IGF1R), apoptosis regulators , oncogenes , and tumor suppressors  [While single SNORD knockout had no or little impact on yeast cells, knocking down the expression of single snoRNAs had severe consequences on zebrafish embryonic development, suggesting that complex metazoan genetic programs require the full potential of ribosome 2′-O-Me . Yet, th., TP53) . Using r., TP53) . Interes., TP53) . These d., TP53) .Importantly, alterations in translational regulation observed in previously described cellular assays could be attributed to ribosomes. This was shown by means of an in vitro cell-free translation assay, in which purified ribosomes were the only variable parameter ,72. WhilrRNA 2′-O-methylation was considered to be a constitutive chemical modification that optimized the functioning of higher eukaryotic ribosomes. Consequently, its role was underexplored in studies aiming at deciphering mechanisms involved in translational regulation. Several recent technical and conceptual breakthroughs have challenged this view and drawn attention to these mysterious modifications: first, the "specialized ribosome" concept, which has fueled new interest in ribosome functioning; and second, rRNA modification detection by omics-based mapping methods and by high-resolution structural techniques. Based on recent technical advances, new evidence supports this novel view of 2′-O-Me in different fields. Indeed, variability in 2′-O-Me and in the expression of 2′-O-methylation factors  and in their contribution to particular cellular phenotypes have been investigated in various physiological contexts, including brain development ,77 and sIn the context of translation, ribosomal diversity induced by 2′-O-Me heterogeneity stands to reason. Translation relies on a delicate molecular process that ensures not only the proper decoding of mRNA and peptide assembly but also the accommodation of a large variety of mRNAs. Consistently, it is not surprising that such a process relies on a variety of ribosomes. Recent publications on rRNA 2′-O-methylation , as wellWithin chromatin, epigenetic regulatory mechanisms rely primarily on chemical modifications of both histones and DNA that modulate the use of the underlying DNA sequence. It is very tempting to establish a parallel with mRNA translation, and thus to propose that rRNA modifications represent a molecular support of an rRNA-mediated epitranscriptomic regulation of mRNA translation. The variation in 2′-O-Me profiles, the identification of potential hyper-sensitive 2′-O-Me sites ,31, and Undoubtedly, recently developed tools to quantitatively analyze 2′-O-Me profiles, to visualize their role in the ribosome structure, and to evaluate translational regulation by ribosome profiling and in vitro translation will be instrumental in breaking the ribosome code.


DNA and RNA have emerged as a material for nanotechnology applications that take advantage of the nucleic acids’ ability to encode folding and programmable self-assembly through mainly base pairing. The two types of nucleic acid have rarely been used in combination to enhance structural diversity or for partitioning of functional and architectural roles. Here, we report a design and screening strategy to integrate combinations of RNA motifs as architectural joints and DNA building blocks as functional modules for programmable self-assembly of a versatile toolkit of polygonal nucleic acid nanoshapes. Clean incorporation of diverse DNA modules with various topologies attest to the extraordinary robustness of the RNA-DNA hybrid framework. The design and screening strategy enables systematic development of RNA-DNA hybrid nanoshapes as programmable platforms for applications in molecular recognition, sensor and catalyst development as well as protein interaction studies. DNA and RNA have been used for nanotechnology applications, though rarely in combination. Here the authors report the use of RNA motifs as structural joints with DNA building blocks for enhanced construction of small multi-component nanoshapes. The fundamental building blocks of nucleic acid architecture, helices and junctions, serve as edges and nodes in the assembly of nucleic acid architectures5 which originate from two fundamentally distinct approaches: the top-down folding of long strands (origami)10, and the bottom-up construction by assembly of autonomously folding RNA modules (LegoTM)12. Rich biological functionality of RNA along with the ability to adopt diverse folds within compact motifs have spurred a new field of RNA nanotechnology13 as well as attempts to create RNA-DNA hybrid nanostructures14. While DNA nanomaterials have been explored extensively as devices for protein binding15, the design of RNA nano-architectures as synthetic scaffolds for protein complex assembly has been approached more recently17. Past efforts to exploit synergies between RNA and DNA in the design of nanomaterials have largely focused on using extensive strand hybridization between the two types of nucleic acids to create structures that are dominated by RNA-DNA hybrid helices14.Nucleic acid nanotechnology aims to design and build functional materials and devices that self-assemble through base pairing and folding of DNA or RNA strandsHere we report a combined design and screening strategy that led to combinations of RNA motifs as architectural joints and DNA building blocks as functional modules for the programmable self-assembly of robust polygonal nucleic acid nanoshapes. The polygonal nanoshapes accommodate topologically diverse DNA modules allowing for broad flexibility to chemically modify, conjugate, or insert protein binding sites, thus furnishing a versatile kit of nano-scaffolds for applications in molecular recognition, sensor and catalyst development as well as protein interaction studies. The partitioning of architectural and functional roles for RNA and DNA modules in the hybrid nanoshapes provides a general blueprint for expanding chemical diversity and functionality of self-assembling nucleic acid nanomaterials.The design strategy for RNA-DNA hybrid nanostructures pursued here seeks to connect RNA motifs that adopt rigid, structurally well-defined folds as topology-defining joints with diverse DNA modules that provide stable components for chemical modification and inclusion of protein binding sites. As key attributes of the RNA-DNA hybrid nanostructures, we aimed for a robust one-step self-assembly process without the need for extensive annealing, high yield efficiency for conversion of nucleic acid modules to assemblies at moderate temperatures, and a set of simple design parameters for facile modification of modules. Our goal was to establish an open platform nano-architecture of self-assembling nucleic acid nanostructures for application and modification by a wide range of users who are not required to be experts in nucleic acid structure or nanotechnology.19. While nucleic acid helices involving such short sequences are marginally stable at room temperature20, formation of overall circularly closed structures contributes stabilization through extensive continuous stacking interactions in the resulting polygons21. We hypothesized that, among combinations of rigid RNA corner motifs with linear DNA inserts, stable assemblies will be preferred that allow formation of circularly closed, polygonal RNA-DNA nanostructures for which we adopted the term nanoshapes22 . A single combination of the RNA corner module with a DNA insert containing 11 base pairs (bp) (RNA-DNA-11) produced clean discrete bands, which indicated the formation of stable assemblies from the nucleic acid components , only the DNA-11 was selectively incorporated with the RNA corner module to form the three discrete RNA-DNA-11 assemblies  on 5% native acrylamide/bisacrylamide (19:1) gels in 2X MOPS buffer  containing 2 mM magnesium chloride. Gels (10 × 10 cm) were run for 1.5–2 h at 220 V, 22 mA. Nucleic acid was visualized under UV light after ethidium bromide staining.Discrete nanoshapes were obtained by extraction of individual bands from PAGE gels. Bands were cut from the gel and divided into smaller pieces. 500 μL of 10 mM sodium cacodylate buffer with 2 mM magnesium chloride were added to extract nucleic acid at 4 °C for 5–7 days. Recovered nucleic acid solutions from band extraction were concentrated on Amicon ultra 0.5 mL centrifugal filters (regenerated cellulose 3000 NMWL).Pre-formation of the triangle with a DNA strand that contains three hybridization sites along with a 3′ single strand extension conjugated with biotin was performed at 37 °C for 5 min in 10 mM HEPES buffer, pH 7, with 2 mM magnesium chloride. Streptavidin (0.2 or 1 eq) was added and incubated at 37 °C for 5 min. The conjugated samples were analyzed by 5% native PAGE and AFM.Pure samples of the isolated nanoshapes were kept at a given temperature . At desired times , 3 μL aliquots were removed and placed on ice. Aliquots were analyzed by 5% native PAGE.29. RNA samples were diluted at 4 °C in assembly buffer  and immediately deposited onto APS-modified mica for 2 min. Typical nucleic acid concentration for deposition was 0.5–1.5 ng/μL. Samples were rinsed briefly with several drops of ice chilled deionized water and dried with a gentle flow of argon. AFM images were collected with a MultiMode AFM Nanoscope IV system (Bruker Instruments) in Tapping Mode at ambient conditions. Silicon probes RTESPA-300 (Bruker Nano Inc.) with a resonance frequency of ~300 kHz and a spring constant of ~40 N/m were used for imaging at scanning rate for about 2.0 Hz. Images were processed using the FemtoScan software package (Advanced Technologies Center). The circumference of the nanostructure was measured and analyzed by tracing the distance along the edge of the shape in the middle of RNA strands.Freshly cleaved mica was modified with 50 mM solution of 1-(3-aminopropyl)-silatrane (APS) in deionized water by immersing strips for 30 min followed by rinsing with deionized water and drying in an Ar streamThermal denaturation melting experiments were performed in a UV-Vis spectrophotometer (Shimadzu UV-2401PC). 900 μL of RNA-DNA hybrid nanoshape sample solution at 0.5 μM concentration was prepared with degassed buffer solution, transferred in a 1 cm quartz cuvette and covered with an oil layer to prevent evaporation. The temperature was raised from 15 to 80 °C at a rate of 0.5 °C per minute using a controlled temperature recirculating water system (Lauda RE 206), measuring the absorption every 1 °C at 260 nm.Further information on experimental design is available in the Supplementary InformationPeer Review FileReporting SummarySource Data


Here we explored the cellular mechanism underlying Bisacodyl cytotoxic effects using quiescent GSC in an acidic microenvironment and GSC-derived 3D macro-spheres. These spheres mimic many aspects of glioblastoma tumors in vivo, including hypoxic/acidic areas containing quiescent cells. Phosphokinase protein arrays combined with pharmacological and genetic modulation of signaling pathways point to the WNK1 serine/threonine protein kinase as a mediator of Bisacodyl cytotoxic effect in both cell models. WNK1 partners including the Akt and SGK1 protein kinases and NBC-family Na+/HCO3− cotransporters were shown to participate in the compound’s effect on GSC. Overall, our findings uncover novel potential therapeutic targets for combatting glioblastoma which is presently an incurable disease.Glioblastoma is a highly heterogeneous brain tumor. The presence of cancer cells with stem-like and tumor initiation/propagation properties contributes to poor prognosis. Glioblastoma cancer stem-like cells (GSC) reside in hypoxic and acidic niches favoring cell quiescence and drug resistance. A high throughput screening recently identified the laxative Bisacodyl as a cytotoxic compound targeting quiescent GSC placed in acidic microenvironments. Bisacodyl activity requires its hydrolysis into DDPM, its pharmacologically active derivative. Bisacodyl was further shown to induce tumor shrinking and increase survival in  Glioblastoma (GBM) is the most common type of malignant brain tumor in adults with a reported incidence of 3–4 cases per 100,000 and a gender preference for male adults .in vivo , WN, WN27], i.e. SPAK  and OSR1 (Oxidative stress-responsive kinase 1) I) are attributable primarily to CO2 diffusion across the cell membrane, conversion of CO2 to H+ and HCO3−, and subsequent intracellular acidification. Then, this acidification is regulated by HCO3− transport I and so directly reflects changes in pHi. This ratio was calculated after background signal subtraction. All experiments were performed at room temperature (22–25° C).Fluorescence measurements on individual cells were performed with an inverted microscope  with an oil-immersion 940 objective , and a quantitative real-time imaging system comprising a cooled CCD camera  and an image analysis software package . Cells were alternately excited at wavelengths of 490 nm (proton-sensitive wavelength) and 460 nm (close to isosbestic point), and emitted light was collected above 510 nm. Pairs of images were acquired every 2.5 sec. Intracellular proton levels and their variations are expressed as the ratio of fluorescence signals (ratio F490/F460); The ratio F490/F460 changes inversely with the change in [H6 proliferating or quiescent  TG1 and TG1-C1 GSC using the TRI Reagent  according to the manufacturer’s instructions. RNeasy mini kit columns (Qiagen) were used for further purification of RNA samples. NanoDrop ND-1000 (Labtech) was used for absorption spectra analysis and RNA purity assessment. Absorption ratios A260/A280 and A260/A230 were comprised between 1.8 and 2.1. RNA concentration was determined using the Qubit fluorimeter and the Quant-it RNA Assay Kit (Invitrogen). RNA integrity was further evaluated with an Agilent 2100 Bioanalyzer and the RNA 6000 LabChip kit. Only RNA with a RNA Integrity Number (RIN) higher than 9 was processed . 1 µg of total RNA was reverse transcribed to single-stranded cDNA using the High Capacity cDNA Reverse Transcription kit . Real-time PCR analysis was performed with individual TaqMan gene expression assays in an ABI Prism 7000HT apparatus  using standard experimental conditions designed by the manufacturer. NBCe 1/SLC4A4 assay ID: Hs00186798-m1. Results were normalized to the 18S rRNA expression levels determined in all conditions (assay ID: 4319413E). Results are shown as mean ± SEM of two independent experiments performed in triplicates.Total RNA was isolated from 5–10×10P values were determined using unpaired two-tailed t-tests to compare two groups or one-way or two-way ANOVA to compare more than two groups. Indications are given in figure legends. The level of significance was set at p < 0.05. Statistical analyses were performed with the Prism 7.0 software (GraphPad).Data were obtained from at least two independent experiments and are shown as mean (± SEM) or mean (± s.d.) as indicated in figure legends.


Classical decision theory postulates that choices proceed from subjective values assigned to the probable outcomes of alternative actions. Some authors have argued that opposite causality should also be envisaged, with choices influencing subsequent values expressed in desirability ratings. The idea is that agents may increase their ratings of items that they have chosen in the first place, which has been typically explained by the need to reduce cognitive dissonance. However, evidence in favor of this reverse causality has been the topic of intense debates that have not reached consensus so far. Here, we take a novel approach using Bayesian techniques to compare models in which choices arise from stable (but noisy) underlying values  versus models in which values are in turn influenced by choices . Moreover, we examined whether in addition to choices, other components of previous actions, such as the effort invested and the eventual action outcome (success or failure), could also impact subsequent values. Finally, we assessed whether the putative changes in values were only expressed in explicit ratings, or whether they would also affect other value-related behaviors such as subsequent choices. Behavioral data were obtained from healthy participants in a rating-choice-rating-choice-rating paradigm, where the choice task involves deciding whether or not to exert a given physical effort to obtain a particular food item. Bayesian selection favored two-way causality models, where changes in value due to previous actions affected subsequent ratings, choices and action outcomes. Altogether, these findings may help explain how values and actions drift when several decisions are made successively, hence highlighting some shortcomings of classical decision theory. The standard way to explain decisions is the so-called valuation/selection model, which includes 1) a value function that calculates desirability for every possible outcome of alternative actions and 2) a choice function that integrates outcome values and generates selection probability for every action. In this classical view, choices are therefore determined (in a probabilistic sense) by hidden values. However, some authors have argued that causality could also be reversed, meaning that values may in turn be influenced by choices. Yet existing demonstrations of reverse causality have been criticized because pseudo-effects may arise from statistical artifacts. Here, we take a novel computational approach that directly compares models with and without the existence of reverse causality, on the basis of behavioral data obtained from volunteers in a new task. The winning model is a generalization of the reverse causality hypothesis, showing that people tend to like more the items that they previously chose to pursue, and even more if they did obtain these items. These effects were manifest not only in desirability ratings but also in subsequent actions, showing that value changes were more profound than just verbal statements. Altogether, our results invite reconsideration of decision theory, showing that actions are not neutral to the values driving them, hence suggesting that the history of actions should be taken into account. Classical decision-making theory states that when facing a choice, agents consider the cost attached to potential actions and the value of their expected outcomes, and select the option that gives the maximal net benefit –5. In thThis reversed logic has been adopted in the well-known cognitive dissonance theory , 8. AccoHowever, this line of research has been recently challenged , 15. IndChen & Risen suggested a clever way to assess this statistical artifact, with a control condition in which both ratings are performed before choices (RRC condition). This control condition has been implemented in several studies, beginning with Chen & Risen themselves, who confirmed that apparent spread of preference is observed even in the RRC condition , 15. To The first aim of the present study was to address this question through a different approach: by comparing computational models in which values are stable versus models in which values can evolve as a function of choice. Using this computational approach, we assessed which model would best account for behavioral data acquired in a new version of the free choice paradigm, following the standard rating / choice / rating sequence.The second aim of our study was to generalize the notion that actions determine values, beyond choice. In decision theory, expected values not only drive which action is selected but also with how much vigor it is performed –30. HereThis logic may extend to the success or failure of the action engaged (whether the outcome was obtained or not), which can be taken as a proxy for the effort invested. Agents may devalue outcomes of actions that were chosen and initiated but not completed, whatever the reason. This post-failure devaluation may account for the case of the fox in the famous Aesop’s fable, who revised his judgment about the desirability of grapes that he failed to reach, leading to the saying “any fool can despise what he cannot get”. This story is often considered as a typical example of cognitive dissonance and received different psychological interpretations: pretending that grapes were sour could for instance attenuate frustration or temper the reputation of being a loser , 35, 36.The third aim of our study was to determine whether choice only impacts declarative judgments or all value-based decisions. We previously showed that rating, effort and choice tasks elicited the same value function , 38. HowHowever, this does not imply that underlying internal values remain stable, as it might be difficult to maintain separate declarative judgments and internal values for a vast collection of items in the long run. Indeed, changes in (explicit) preferences have been shown to persist for one week  and up tTo recapitulate, we designed a new free-choice paradigm that alternates rating tasks, in which participants make judgments about the desirability of food items, and effort tasks, in which they decide whether or not to produce handgrip force to obtain these items . Differemax). This is an indicator that participants did try to reach the target and get the item. Conversely, in Exp 3, choice was explicit: participants could accept or decline the offer (by pressing ‘yes’ and ‘no’ buttons) and then squeezed the grip to try and get the item. Other changes were introduced as additional controls. Notably, in Exp 2–3, 30 additional items were rated but not presented in the choice task, to assess the exposure effect . Also, the pairing of food items and force targets was constant in Exp 1 but redrawn in Exp 2–3, to avoid participants just repeating the same choice instead of evaluating the offer. Other differences were minor and meant to improve the design efficiency, although in the end, they did not produce much of an improvement.Three groups of participants  were recruited to participate in slightly different versions of our new free-choice paradigm . Individual regression estimates (betas) were then entered into group-level random-effect analyses. For success, only accepted trials were included . For force, only successful trials  were included. As expected  would result from a cost/benefit trade-off, the cost being here associated with physical effort, while the benefit varied with the value of items presented as potential outcomes . We tookexpected , ratingsAs in usual free-choice paradigms, we expected post-choice ratings (relative to pre-choice ratings) to be higher for chosen items than for unchosen items. In other words, the choice variable should have a positive influence on the change from pre-choice to post-choice rating . We also tested the influence of the additional action-related factors that we integrated in our paradigm. According to the so-called ‘sour-grape’ effect, post-choice ratings should be higher for earned items  than for lost items , predicting again a positive influence of success on Δ-rating. Finally, according to the so-called ‘fruit of labor’ effect, the amount of effort expenditure should also have a positive influence on Δ-rating.C = 0.09±0.01; βS = 0.04±0.01, both p<0.001). This means that participants rated items higher after deciding to obtain these items, and beyond this effect, after successfully achieving the required force level. Note that even if we changed the definition of choice in Exp1/2 versus Exp3, and the pairing between ratings and targets in Exp1 versus Exp2/3  and not significantly different between experiments (p = 0.389). Finally, there was no significant effect of exerted force  and the intercept was not different from 0 . Thus, we did not validate the hypothesis of a ‘fruit of labor’ effect, making items more valuable when they are obtained with more effort. Also, there was no evidence for a drift in rating, independent of task factors .To test these three predictions, we computed Δ-rating for each participant (ratings were z-scored within subjects before computing the difference), each item, and each repetition . This Δ-rating was then linearly regressed against choice C, success S, and force F as predictors, pooling together the two repetitions. In order to orthogonalize regressors, all trials were z-scored within subjects for choice, while only chosen trials were z-scored for success (unchosen was coded 0) and only successful trials were z-scored for force (unsuccessful was coded 0). We also included a constant intercept term T that captured the effect of time. Individual regression estimates were then entered into group-level random-effect analyses . The effAs all tasks were self-paced, one may wonder to what extent duration of exposure could be a confound, as difficult trials could take longer and thus prolong the exposition to related food items. In order to address this concern, we re-ran the same analysis but including cumulative duration of exposure (computed for each item at each rating) as an additional regressor. Critically, this regressor was not significant (p = 0.533) and the pattern of results was not modified.Finally, we assessed whether the change in rating  was driven by chosen items being rated higher, or unchosen items being rated lower, or both. We took advantage of the 30 items that were rated but randomly excluded from the effort task in Exp 2-3. Critically, Δ-rating for excluded items (+0.03) was in-between that of chosen items (+0.10) and unchosen items (-0.07), with a significant difference in both cases (both p< 0.001). Relative to excluded items, there was no difference in the magnitude of Δ-rating induced by acceptance and rejection (p = 0.194). Similarly, there was no difference in Δ-rating between excluded items and selected items .Thus, model-free analyses provided evidence for an influence of choice and success on likeability ratings. However, these effects remain susceptible to the same statistical artifact (regression to the mean) as in the classical free choice paradigm. In addition, the complex interplay between experimental variables and behavioral measures was not properly assessed in the above model-free analyses that tested the different effects separately. To better assess whether the effect of past actions reflected an actual change in the underlying values, we therefore turned to a computational approach. As there was no evidence for a change in behavior across experiments, we pooled all participants in the following model-based analyses.i and Vi are respectively the rating and value of item i, and ε is a Gaussian noise with variance i and ε), therefore allows computing a likelihood that all changes in ratings are due to mere chance.The general strategy was to formalize the null hypothesis, in which ratings are solely noisy observations of hidden values, and choice effects on ratings only statistical artifacts, and compare this null model to models that integrate the influence of past behaviors. The null model can be written as follows:Ri=Vi+εwhere RiIn the following, we detail a set of alternative models that could account for the influence of past actions on subsequent behaviors , as in the classical free-choice paradigm. We start by presenting the equations used to capture the direct bias that past actions may exert on next ratings.As in model-free analyses, the effort task was decomposed into three behavioral variables: choice Then, total bias C, bs, and bF represent respectively the weight of choice, success, and exerted force. The parameter bT captures the effect of time  and allows the model to capture non-specific trends like boredom (negative effects) or hunger (positive effect).The free parameters bFinally, the hypothesis that these action-related variables could affect subsequent ratings can be written as:C, bS, bF, and bT are (strictly) set to 0, i. Conversely, if bias parameters b are allowed to differ from zero, then ratings will consistently change according to behavioral variables derived from the effort task, on top of spurious fluctuations driven by the noise term. Switching on or off the four bias parameters resulted in 16 different models. In order to test the possibility that actions have an impact on subsequent ratings (hypothesis H1), we grouped with H0 the model containing only an effect of task repetition  and considered as belonging to H1 all other models that included at least one effect of choice, success, or force (at least one b ≠ 0 other than bT).When all parameters bNote that A family-wise model comparison , 40 provThis model-based analysis demonstrated that ratings were actually modulated by two action-related variables of the preceding effort task: choice and success. Indeed, higher ratings were assigned to items for which the trial was accepted (meaning that the subject decided to try and reach the target) and for which the item was earned (meaning that the subject succeeded in reaching the target). However, these effects may be short-lived and only affect ratings provided just after the effort task. In the next section, we examined whether the choice and success effects could extend to behaviors beyond the next immediate rating.We first assessed whether actions would affect not only the subsequent rating session (from E1 to R2 or E2 to R3), as in the classical free-choice paradigm, but also the distant rating session (from E1 to R3). For this purpose, the model was extended to allow action-related biases to accumulate across sessions of the effort task:This equation makes similar predictions to A family-wise comparison between H0 (2 models), H1 (14 models), and H2 (14 models) sets showed that H2 provided the best explanation of the data , suggesting that actions had a lasting effect on distant ratings. Furthermore, as in previous analyses, grouping models by action-related variables showed that choice and success bias, but not force bias, were significantly present in the population .Although this analysis suggests that actions have a lasting effect, it does not imply that this effect would affect other value-driven behaviors than ratings. In other words, the effect could only change declarative judgments, with no influence on subsequent actions and related markers .The question here is to assess whether past actions can influence not just rating but a common hidden value that would drive behavior in both the rating and effort tasks. For this purpose, we needed a quantitative model of how value drives choice, success and force. Inverting this model could then provide evidence that observed choice, success and force data were generated by constant values versus values evolving under the influence of past actions. Following our framework, we modelled all action-related behaviors  as resulting from a cost/benefit trade-off.F) is some Gaussian noise, ρX, ηX and the offsets X0  are free parameters that were estimated through Bayesian inversion. Focusing for example on choice, 0)) if ρCV + ηCL > 0, i.e. if the benefit  is higher than the required cost (force target). As a sanity check, we verified with t-tests that ρ parameters were significantly positive, irrespective of the considered hypothesis  and the benefit  involved in every trial. Formally, dropping the indexing of items (i) and repetitions (k) for the sake of readability, we have:Critically, in this new set of alternative models, the biases induced by past actions  during task k, and V1 is a free parameter that captures the initial value of this item. The dynamical values (Vk) were then used to predict not only ratings, using k. In fact, the predicted ratings are the same as in the previous set of models, because combining Eqs Where VWe could not compare H3 directly to H1-H2 models as they were formulated in previous sections, because Bayesian model selection can only be performed between models fitted to the same data. Yet previous model comparisons exclusively considered rating data, while the additional prediction brought by H3 is about choice, success and force data. Thus, we rephrased H1 and H2 by including Eqs A family comparison including all models (H0 to H3) showed that indeed H3 best explained the data . Post-hoc analyses of the fitted bias parameters in H3 confirmed a positive effect of past choice and success on underlying value, corroborating our previous results, and a non-significant effect of past force. Furthermore, extending models for H1 and H2 did not alter previous conclusions, as significant effects reported in previous sections were still present see .Finally, we verified that our Bayesian model comparison approach was indeed immune to the ‘regression to the mean’ artifact. For this purpose, we ran Monte-Carlo simulations to a) generate mock behavioral data under the null hypothesis H0 and then b) estimate the effect of past actions in these random data under H1, H2 or H3 see . This reCritically, these simulations show that our Bayesian approach did not inflate the amplitude  nor the significance  of bias parameters, as it would be the case with classical analyses see  Tables. In this paper, we examined the possibility of reverse causality from actions to the underlying values that drive these actions. This idea has a long history and has been notably defended in the context of cognitive dissonance theory , 8. We sThe cornerstone of cognitive dissonance theory is the free choice paradigm, which implements a choice-rating-choice series of tasks. The classical result that has been repeatedly observed is that choice seems to affect the change from first to second ratings assigned to the two items. The critique raised by Chen & Risen  has castTo directly address this issue, and rather than introducing a new experimental control condition, we utilized a novel computational strategy that simply compare models with and without an effect of choice on rating. This involves using Bayesian model inversion and comparison techniques to derive the plausibility of an effect beyond what can just be explained by noise in rating and choice behaviors –44. ThisAlthough we kept the term choice to underline the link with the existing literature, our choice task was quite different from the typical free choice paradigm. Instead of expressing a preference between two items, participants decided whether or not to exert a given force for a particular food item. The spread of preference was therefore measured between items for which participants made an effortful attempt and the others. We observed no significant impact of the way choice was expressed in the different versions of the paradigm (pressing on accept / decline buttons versus just trying or not to reach the target). This null result suggests that choice does not have to be explicit in order to induce spread of preference. Beyond choice, our task was designed in order to incorporate two candidate effects of actions on values: the so-called ‘sour grape’ and ‘fruit of labor’ effects.As the grapes in Aesop’s fable, some food items were paired with unreachable force levels, thereby introducing cases of failure. We indeed found that, as the famous fox, our subjects rated items that they failed to obtain as less desirable than initially judged. The usual interpretation for the fox despising what he could not get is that he is trying to avoid regret or humiliation, and maintain the illusion that he is in control. However, following the idea of reverse causality, it could also represent a true change of preference. Indeed success may be a rough proxy for the amount of resources deployed, which should scale with the desirability of the goal. Thus, the brain would logically conclude from observing failure that the goal value is lower than initially estimated. This inference might represent an adaptive mechanism: decreasing the value of unreachable goals could save time and energy. The implication is that updating value would be easier or more efficient than monitoring action feasibility. Yet exploring the environments in which this speculative statement is correct would require comprehensive simulations, using an evolutionary game theoretical approach. Finally, we note that, even if we focus in this discussion on the effect of failure to push the analogy with the sour grapes fable, our model-based analysis does not distinguish between failure and success effect (or accept and decline effects for choice). Thus, all we can conclude is that relative to the initial difference, the difference in desirability between obtained and missed items tends to increase.Regarding effort expenditure, the reverse causality hypothesis would predict a positive effect of force produced on value, since deploying more resources would signal a more desirable goal. This sort of inference would explain what has been coined ‘fruit of labor’ or ‘effort justification’ effect–the fact that a reward is much appreciated when it comes as an output of strenuous effort . By exteMore generally, cognitive dissonance theory invokes self-consistency mechanisms to account for the influence of choice on rating. The idea is that agents align their ratings onto their choices because they want to maintain coherence (reduce dissonance), either for themselves or for other people (experimenters). Although this mechanism has long been considered subconscious, it was recently suggested that it might require an explicit memory of the choices made , 47. HerYet this assumption of explicit adjustments may be tempered by the observation that past actions modulated not only subsequent ratings but also next choice, success and force outputs. Notably, adjusting force just for the sake of showing coherence would entail a deterrent cost. Moreover, keeping in mind all past behaviors, so as to ensure coherence with current behavior, would rapidly become intractable. Updating one value that drives all behaviors appears as a more reasonable strategy, and a more parsimonious explanation. This is even more critical for cognitive dissonance effects that were shown to last for days to years , 20. ValHowever, there are a number of limitations in our study. A first limitation is that we did not consider the possibility that overt ratings may be processed similarly to other actions, eventually resulting in some sort of rating-induced value changes. This was omitted for the sake of simplicity but in principle, people could get information about their values from their own statements. A second limitation is that in our design, choice was always expressed actively. Indeed, to accept an offer, participants had to lightly squeeze the grip (in Exp 1) or to press a button (in Exp 2 and 3). In other words, we did not include a "no-go" condition in which acceptance would be indicated by inaction. Different results might have been obtained in this condition, since it has been shown that positive and negative items are revaluated differently depending on whether choice is active or inactive , possiblOne natural solution would be Bayesian updating: value should be updated according to (i) its precision: the higher the confidence associated to the value of an item, the less susceptible to change it should be, (2) the prediction error: the influence of a choice should be lower if it was strongly predicted by value. Note that choice and success are binary (0 or 1), so they necessarily differ from their prior probability. Consistent with the latter principle, it has been shown with the free choice paradigm that easy choices  have a lesser influence on rating change than hard choices . The forTo make sense, such a model would need to assume some encapsulation of the brain systems that generate action and those that update value. If the latter system were fully informed about the computations performed by the former system, there would be no discrepancy between observed and predicted behavior, and therefore no possibility of learning. With two separate systems, one could learn from the other: the value-updating system would integrate a rough initial prediction from a superficial inspection of the choice situation, and then learn from the discrepancy between that prediction and the eventual behavioral response generated by the action-selection system after a more careful consideration.In summary, we have provided a computational method to test the effects of actions on underlying values while properly controlling for statistical artifacts. Using this method, we have extended the classical effect of choice on likeability judgment, showing that not only choice but also experience of success versus failure may modulate the hidden values that in turn impact not only preference but also subsequent effort expenditure and eventual outcomes. Altogether, this work generalizes the notion of a two-way dynamic interaction between actions and values, which may invite a serious reconsideration of decision theory.The research has been approved by the Ethics Committee for Biomedical Research (‘Comité de Protection des Personnes’) of the Pitié-Salpêtrière Hospital. All participants gave written informed consent prior to participating in the study.Three groups of participants  were recruited from a volunteer database in Paris to participate in experiments 1 to 3. They were asked to refrain from eating at least 3 hours before arriving in the lab, but were allowed to drink water . On average their last meal was 5h43±51min, 6h18mn±42min and 5h48±39min before the start of the study. They received 30 euros for their participation and up to two food products, corresponding to the two trials that were drawn at random at the end of the two effort tasks. Before the experiment, participants were shown a large subset of the potential food prizes stored in the testing room. They were then informed that they could only get the food items that they successfully obtained during the task, and that there would be a lottery to select the two trials that determined their food reward. Three participants were excluded because they had too few failures , meaning that the effects of choice and success were not separable. The analysis was therefore conducted on a total of 63 participants.www.mathworks.com) and Psychtoolbox . Food products were photographed frontally over a black background, with some of the contents displayed in front of the packaging. Size of the photographs was 400x300 pixels. All experimental stimuli were presented via MATLAB (https://www.vernier.com) were used in Exp 2–3.A handmade pneumatic handgrip device was used in Exp 1 (as in Ref 34), whereas Vernier Hand Dynamometers  of each hand as participants squeezed the grip as strongly as possible for 3s. This subject-specific, hand-specific measure was used to calibrate target force levels in effort task trials. Subsequently, participants performed a series of two tasks: rating (R) and effort (E) tasks alternated following a R1-E1-R2-E2-R3 order. During the rating task, participants judged the desirability of all food products. During the effort task, participants were presented with a food item paired with a target force level and had to make squeeze/no squeeze decision to earn or reject the item. Participants were not told in advance that these tasks would be repeated. In all tasks, participants responded at their own pace.For force calibration, we separately measured the maximum force level . Participants were shown an image of a food item indicated on a visual analogue scale (VAS) the extent to which they desired to eat the food item . They wemax. To ensure that target force level and desirability rating were uncorrelated, we formed a diamond-shaped pairing  whilst the middle-ranked items were paired with levels around 20% or 120% Fmax. Furthermore, we paired adjacent ranked items with force levels symmetrically spaced above and below the midpoint. The effort-rating pairing was the same for the first and second effort task (E1 and E2), but the order of item presentation was randomized within each effort session and for each participant.Effort task . Based on subject-specific ratings in the first session (R1), we excluded the 15 lowest and 15 highest ranked products and used the remaining in the effort task. Each item was paired with a given target level of force, between 20% and 120% Fring see , such thmax). Squeezing the grip moved the red bar that served as a visual feedback on the force produced. Participants had the opportunity to earn the food item by maintaining the bar above the target force level for at least 4.5s consecutively. Success was confirmed by a green frame around the food item for 2s. At any point, participants could press a 'skip' key on the keyboard using their non-squeezing hand to reject the food item, in which case the item was crossed out but remained on screen for 2s. Inter-trial interval was 1-2s, uniformly distributed.The critical outcomes in the effort task are choice, success, and amount of exerted force. Each trial began with 1s acquisition of force baseline levels, during which participants were told not to squeeze, and 1s fixation cross. Participants were then presented with one food picture at the center of the screen and an image of an empty thermometer next to it . At this time, the target force level was not indicated, but participants could disclose it by lightly squeezing the handgrip (5% FFmax). Conversely, the trial was considered as rejected if the participant pressed the skip button without producing even this minimal force. The other behavioral variables, success and force, were defined only for accepted and successful trials respectively, in the aim of decorrelating them from the choice variable.In addition to the force produced and the eventual skip or success outcome, we defined choice as the attempt to obtain the outcome: the trial was considered as accepted if the participant produced the minimal target force level , participants understood that they would receive one food item randomly selected amongst those with which the target force levels were successfully reached. In total participants received two items, one from each of the two effort tasks.Exp 2 was very similar to Exp 1, except for the following changes.In the rating task, we used 150 items instead of 120, leading to 150 rating trials.Fmax) in Exp1. Alternatively, pressing the ‘no’ button allowed declining the offer and proceeding directly to the next trial (without seeing the target force level). This change was implemented in order to avoid the possibility that participants accidently pass the 20% Fmax threshold while they only intended to disclose target force level (corresponding to 5% Fmax). (5) Finally, before each effort task session, participants were informed in Exp 2 that one trial would be randomly selected and realized, meaning that they would either get the food item or nothing depending on whether or not they successfully reached the target force level. This payoff schedule was different from Exp 1, where one successful trial was randomly selected and realized, leaving participants the liberty to decline all food items but the one they prefer. Fortunately, none of the participants employed this risky strategy, even in Exp 1 .In the effort task , several changes were made. (1) We randomly selected 30 food items from the rating task to be excluded, in addition to the 15 lowest and 15 highest ranked products. The goal was to estimate how declarative judgments of desirability may drift, independently from any choice or effort production. (2) Different pairings between target force level and desirability rating were used in the two sessions of the effort task (E1 and E2). The goal was to avoid repetition effects between E1 and E2 and to ensure that participants would evaluate the cost/benefit tradeoff even in the second session. Therefore, for each participant, items and targets were pseudo-randomly paired so as to orthogonalize not only force level and desirability rating but also force levels used in E1 and E2 for the same item. (3) In order to reduce fatigue, the minimal above-target duration required to earn the item was 3s in Exp 2 (instead of 4.5s in Exp1). (4) The action required to disclose target force level was pressing a ‘yes’ button in Exp 2 instead of a light squeeze on the handgrip (5% Fmax). This explicit commitment made a difference: the rate of failure  was lower is this version of the task compared to the two first versions. Despite the low number of data points, we did observe significant success effects on subsequent ratings in this last version. However, it might not be ideal to investigate the sour-grape effect, because the statistical power of comparison between success and failure was quite weak.Exp 3 was similar to Exp 2 except for further changes in the effort task. (1) Both food item and target force level were presented, simultaneously, at the beginning of the trial. Then participants could accept or reject the offer, by pressing either the ‘yes’ or ‘no’ button. Thus, acceptance was indicated explicitly, compared to the light squeeze criterion (>20%www.mathworks.com). Computational modeling, estimation, and simulation, as well as follow-up Bayesian analyses [http://mbb-team.github.io/VBA-toolbox/). Regression coefficients are given as mean + sem. Goodness of fit is the balanced accuracy for logistic regression  and R2 for linear regression (force), also given as mean + sem. All t-tests are two-tailed. Details on computational models are provided in the results section.All analyses were run with Matlab Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.


Camels possess the characteristics of salt- and drought-resistances, due to the long-time adaption to the living environment in desert. The camel resistance research on transcriptome is rare and deficient, especially reabsorption in renal cortex. Non-coding RNAs are normally considered as the RNA molecules that are not translated into proteins, their current roles remain mostly in regulation of information flux from DNA to protein, further on normal life activities and diseases. In order to reveal the mysterious veil of the post-transcriptional regulation of ncRNAs in renal cortex for the first time as far as we know, we designed and carried out the experiment of salt stress and water-deprivation stress in camel.Camelus bactrianus), we identified certain significantly differential RNAs, including 4 novel lncRNAs, 11 miRNAs and 13 mRNAs under salt stress, 0 lncRNAs, 18 miRNAs and 14 mRNAs under water-deprivation stress. By data analysis, the response pathway of post-transcriptional regulation concerning salt and water-deprivation stresses was put forward, involving preventing sodium from entering the cell, purifying of water and compensating neutral amino acids by miR-193b, miR-542-5p interaction with SLC6A19 mRNA.By means of RNA-seq in renal cortex of Alxa Bactrian Camel  contains supplementary material, which is available to authorized users. RNA degradation and contamination were monitored on 1% agarose gels. RNA purity was checked using the NanoPhotometer spectrophotometer . RNA concentration was measured using Qubit RNA Assay Kit in Qubit 2.0 Fluorometer . RNA integrity was assessed using the RNA Nano 6000 Assay Kit with the Agilent Bioanalyzer 2100 system .A total amount of 3 μg total RNA per sample was used separately as input material for the small RNA and lncRNA library. Sequencing libraries of small RNA were generated using NEBNext Multiplex Small RNA Library Prep Set for Illumina . For lncRNA library preparation, firstly, ribosomal RNA was removed by Epicentre Ribo-zero rRNA Removal Kit , and rRNA free residue was cleaned up by ethanol precipitation. Subsequently, sequencing libraries of lncRNA were generated using the rRNA-depleted RNA by NEBNext Ultra Directional RNA Library Prep Kit for Illumina .The clustering of the index-coded samples was performed on a cBot Cluster Generation System using TruSeq SR Cluster Kit v3-cBot-HS (Illumia) for small RNA and TruSeq PE Cluster Kit v3-cBot-HS (Illumia) for lncRNA. By pooled RNA-seq , the libCamelus Bactrianus genome by Bowtie [Bos Taurus database, target gene prediction by miRanda, GO and KEGG pathway enrichment analyses of target genes by GOseq [C. Bactrianus genome by TopHat (v2.0.9) [C. Bactrianus and Bos Taurus databases, differential expression analysis by Cuffdiff (http://cole-trapnell-lab.github.io/cufflinks/cuffdiff/index.html), target gene prediction by lncRNA gene upstream/downstream 100 kb and Pearson Correlation Coefficient [The analyses procedures of miRNA data were as follows: quality control, reads mapping to y Bowtie , novel my Bowtie  and mirdy Bowtie , differey Bowtie  and DEGsy Bowtie , small Rby GOseq  and KOBAby GOseq . The ana(v2.0.9) , transcr(v2.0.9) , lncRNA (v2.0.9) , CPC (0.(v2.0.9) , Pfam Sc(v2.0.9) , 42, Phy(v2.0.9) , mRNA anfficient , GO and fficient  and KOBAfficient .SLC6A19, miR-193b and miR-542-5p. We are hoping to provide a theoretical basis for healing disease that is similar to high blood pressure for humans. Due to the defects in the camel genome function, we selected the database of the bovine which is close to the camel for the annotations of lncRNA and miRNA in this experiment, so we still need more evidences to optimize the results in the future .Based on the lncRNA, miRNA, and mRNA data by RNA-seq and incorporated previous studies, we identified four novel salt-resistance-related lncRNAs in renal cortex and proposed the ncRNAs-related post-transcriptional regulation pathway to explain how camels respond to salt stress and water-deprivation stress for the first time, in light of differentially expressed Additional file 1: Table S1. The differentially expressed mRNAs, miRNAs and lncRNAs of renal cortex under salt stress. Table S2. The differentially expressed mRNAs and miRNAs of renal cortex under water-deprivation stress. Table S3. Sequence of significantly down-regulated four novel lncRNAs in the renal cortex of camel under salt stress.Additional file 2: Figure S1. Normalized mean plasma Na+ concentration of camel under salt stress, water-deprivation stress and free diet.