Instructions given prior to extinction training facilitate the extinction of conditioned skin conductance (SCRs) and fear-potentiated startle responses (FPSs) and serve as laboratory models for cognitive interventions implemented in exposure-based treatments of pathological anxiety. Here, we investigated how instructions given prior to extinction training, with or without the additional removal of the electrode used to deliver the unconditioned stimulus (US), affect the return of fear assessed 24 hours later. We replicated previous instruction effects on extinction and added that the additional removal of the US electrode slightly enhanced facilitating effects on the extinction of conditioned FPSs. In contrast, extinction instructions hardly affected the return of conditioned fear responses. These findings suggest that instruction effects observed during extinction training do not extent to tests of return of fear 24 hours later which serve as laboratory models of relapse and improvement stability of exposure-based treatments. However, about one third of patients undergoing exposure-based treatments may not experience a clinically relevant decline in their pathological anxiety3 and another third may experience a relapse, i.e. a return of their pathological anxiety, within 10 years4. These findings highlight the relevance of determining factors that moderate both short-term and long-term outcomes of exposure-based treatments. Pavlovian fear conditioning paradigms allow for the investigation of the development, treatment and maintenance of fear under laboratory conditions and typically comprise several experimental phases5: During fear acquisition training, a previously unrelated stimulus  is presented together with an aversive event , acquires signal value for the US and eventually elicits a conditioned fear response (CR). During extinction training, the CS is presented without the US and the CR gradually declines which is why extinction procedures serve as a laboratory analogue for exposure-based treatments6. Subsequent retention tests which entail the re-exposure to the CS after experimental manipulations and/or a period of time are used to investigate the maintenance of the extinction memory trace. Thus, retention tests are used to model long-term stability of fear reduction and relapse after exposure-based treatments7.Exposure-based treatments of pathological anxiety, which involve confronting patients with their feared stimulus or situation until the fear response declines8 as well as when given prior to extinction training9. Instructions given prior to extinction training serve as a laboratory analogue for cognitive interventions which often accompany exposure treatments, e.g., in form of guided threat reappraisal10. In general, instructions informing participants about the subsequent non-occurrence of the US seem to facilitate extinction learning across different outcome measures9. So far, however, research on this topic mostly focused on conditioned skin conductance responding (SCR) and found that instructions often induce an immediate extinction which can be observed even in the first trial of extinction training13. Facilitating effects of instructions have been observed for the extinction of conditioned fear-potentiated startle responses (FPS) as well16, whereas conditioned CS valence ratings seem to be somewhat immune against instructions15. In addition, the removal of the physical threat  does not seem to moderate the influence of verbal instructions on extinction learning as indexed by SCRs and conditioned valence ratings13, but its effects on the extinction of conditioned FPSs as well as on extinction retention have never been systematically investigated.Verbal instructions about CS-US associations influence conditioned responding when given prior to acquisition training17 or signal18 learning as indexed by conditioned SCRs19 and US expectancy ratings20, affective learning as indexed by conditioned FPSs21, and evaluative conditioning as indexed by conditioned CS liking or valence ratings22. According to these assumptions, instructions given prior to extinction may immediately establish a CS-noUS association as expressed by indicators of relational learning, whereas affective learning is facilitated but additional congruent experiences may be needed to abolish defensive responding. The physical threat removal helps to establish a predictable, safe context23 and, thus, may increase the effects of verbal instructions on affective learning during extinction training as indexed by FPSs. Finally, the liking of the CS which signaled the US in the past  is hardly affected by verbal instructions unless specifically targeted with positive information about the CS24.Differences between outcome measures have been attributed to the multiple processes involved in fear learning, i.e., cognitive relational11 or instructions targeting CS valence24 on reinstatement of conditioned fear and found no reinstatement of differential SCRs in either group, but reinstatement of conditioned FPS in both groups independent of instructions11. Another study25 found increased extinction retention only for a group in which safety information was given not only prior to extinction training on day 1, but also repeated prior to the retention test on day 2. Here, however, conditioned responding was measured only with SCRs, although research on the effects of instructions on extinction learning cited above suggests differential effects depending on the outcome measure. In addition, physical threat removal prior to extinction training may moderate subsequent extinction retention depending on whether the threat is present during the retention test or not.In contrast to these short-term effects, research on the effects of verbal instructions given prior to extinction training on the return of fear is sparse which limits the potential clinical relevance of these findings. Two studies used between-group designs (instruction vs. no instruction) to investigate the effects of either contingency instructions prior to extinction training7, we had no specific hypotheses for different outcome measures.Thus, we conducted a differential cue conditioning study in which acquisition and extinction training took place on day 1 whereat one group received no instructions prior to the extinction training , another group was informed that no further US will be applied during subsequent trials  and in a third group we removed the physical threat in addition to the verbal instruction . On day 2, we tested spontaneous recovery of the CR by re-exposing all groups to the CSs first in the absence of the physical threat, i.e., without the US electrode attached, then again in presence of the physical threat, i.e., with the US electrode attached. Then an unsignaled US was presented to test the effects of extinction instructions on reinstatement of fear. Skin conductance and fear-potentiated startle responses were measured during all experimental phases and CS valence ratings were obtained after each of the experimental phases  = 6.674, p = 0.001, partial R² = 0.080) but not trial type  significantly affected startle magnitude. Sidak-corrected pairwise comparisons confirmed that the UE group showed generally smaller startle magnitudes than the VIE  and the VIE-R group  during pre-conditioning. Testing the raw scores during the pre-conditioning phase confirmed these findings, i.e., significant main effect of instruction group  = 6.303, p = 0.002, partial R² = 0.161) and Sidak-corrected pairwise comparisons . Thus, we took the average responding during pre-conditioning into account as a covariate for all subsequent tests on startle magnitudes during acquisition and extinction training.A linear mixed model testing the fixed effects trial type (CS+ vs. CS- vs. ITI) and instruction group (VIE vs. VIE+ R vs. UE) during the acquisition training revealed that startle magnitudes were significantly affected by trial type  = 103.551, p < 0.001, partial R² = 0.359), trial number  = 57.533, p < 0.001, partial R² = 0.570) and their interaction  = 2.360, p < 0.001, partial R² = 0.047), but not by the instruction group  = 1.176, p = 0.309) when controlling for the average responding during pre-conditioning and its association with the experimental groups. Follow-up linear mixed models testing either CS+/CS- differentiation or CS+/ITI potentiation confirmed that acquisition training led to an differentiation between CS+ and CS−  = 25.864, p < 0.001, partial R² = 0.069) which progressively increased  = 2.618, p = 0.003, partial R² = 0.039) as well as a pronounced potentiation of startle responses elicited during CS+ in comparison with those elicited during the ITI  = 210.172, p < 0.001, partial R² = 0.548) that developed during acquisition training  = 2.127, p = 0.016, partial R² = 0.032); see Fig. A linear mixed model testing the fixed effects trial type and instruction group as well as the fixed effect trial number (to account for learning effects) during l type  = 22.737, p < 0.001, partial R² = 0.085), trial number  = 57.343, p < 0.001, partial R² = 0.583) and their interaction  = 2.800, p < 0.001, partial R² = 0.100). In addition, instruction groups differed both in their general response magnitudes during extinction training  = 19.455, p < 0.001, partial R² = 0.081) as well as dependent on trial type  = 4.835, p < 0.001, partial R² = 0.036) and trial number  = 4.923, p < 0.001,, partial R² = 0.100) when controlling for the average responding during pre-conditioning and its association with the experimental groups. Sidak-corrected pairwise comparisons revealed that the UE group showed generally higher startle magnitudes than the VIE  and the VIE-R group  during extinction training.A linear mixed model testing the fixed effects trial type and instruction group as well as the fixed effect trial number (to account for learning effects) during F = 14.576, p < 0.001, partial R² = 0.117) driven by pronounced startle potentiation during both CS+ and CS− presentations compared to ITIs , a small effect in the VIE group  = 3.427, p = 0.034, partial R² = 0.037) driven by startle potentiation during CS+ presentations compared to ITIs  and a non-significant effect in the VIE-R group  = 2.947, p = 0.059); see Fig. Following up on significant interactions between instruction group and trial type respectively trial number, we computed two further linear mixed models per instruction group, one testing for the effect of trial type and the other testing for the effect of trial number. The first set of models revealed a medium effect of trial type in the UE group  = 44.003, p < 0.001, partial R² = 1.195), followed by the VIE-R  = 11.714, p < 0.001, partial R² = 0.364) and the VIE group  = 8.945, p < 0.001, partial R² = 0.278). Sidak-corrected pairwise comparisons using the last trial of extinction training as reference confirmed different response reduction time courses in the different groups, that is in the UE group response magnitudes up to the 5th trial were significantly different from the 12th trial , whereas in the VIE group significant differences compared to the 12th trial were observed up to the 3rd trial  and in the VIE-R group up to the 2nd trial of extinction training ; see Fig. The second set of follow-up models revealed significant effects of trial number in all three instruction groups with the largest effect in the UE group  = 18.490, p < 0.001, partial R² = 0.356), instruction group  = 5.197, p = 0.007, partial R² = 0.173) as well as their interaction  = 3.269, p = 0.013, partial R² = 0.126). Follow-up linear mixed models conducted within instruction groups revealed a large effect of trial type in the first trial of extinction training in the UE group  = 14.576, p < 0.001, partial R² = 0.757) driven by pronounced startle potentiation during both CS and CS- presentations compared to ITIs , a significant effect in the VIE group  = 4.839, p = 0.011, partial R² = 0.318) again driven by potentiation during both CS+ and CS− presentations compared to ITIs  and a non-significant effect in the VIE-R group  = 2.947, p = 0.059). However, a Bayes-factor of 0.57 for the VIE-R group offers only limited support for the null hypothesis.Additionally, we investigated immediate extinction effects by testing the fixed effects trial type and instruction group for the first extinction trial only and found significant main effects of trial type . Bayesian one-way ANOVAs with the repeated measure trial type revealed Bayes factors of 0.09 (UE), 0.02 (VIE) and 0.03 (VIE+ R) which confirmed a complete extinction of conditioned fear-potentiated startle responses in all experimental groups as a baseline for return of fear tests on day 2.Critically, during the last two trials of extinction training neither trial type nor instruction group or their interaction significantly affected startle magnitude  = 12.422, p < 0.001, partial R² = 0.032) and, most strongly, by the reattachment of the US electrode  = 405.256, p < 0.001, partial R² = 1.133). Sidak-corrected pairwise comparisons revealed that startle magnitudes elicited during re-exposure to the CS+ were higher than those elicited during CS- presentations  and ITIs . We also observed a small main effect of instruction group  = 3.819, p = 0.022, partial R² = 0.027), however, Sidak-corrected pairwise comparisons failed to confirm significant differences between groups. We did not observe any significant interactions between instruction group, trials type and reattachment of the US electrode .Linear mixed models testing the fixed effects trial type, reattachment and instruction group on startle magnitudes during re-exposure to the CSs 24 hours after extinction training were affected by trial type  = 3.954, p = 0.020, partial R² = 0.025) even though the US electrode was not even reattached. Sidak-corrected pairwise comparisons revealed that the effect of trial type during the first re-exposure to the CSs was mainly driven by increased startle responses during CS+ compared to CS- trials  and to a lesser degree by a potentiation of CS+ responses compared to ITIs ; see Fig. Although already suggested by the non-significant interaction between trial type and reattachment of the US electrode, we specifically tested return of fear during the first re-exposure to the CSs and found a small effect of trial type  = 4.886, p = 0.008, partial R² = 0.043) and, most pronounced, of reinstatement  = 16.228, p < 0.001; partial R² = 0.070) but no significant interactions between these fixed effects or with the instruction groups . Sidak-corrected pairwise comparisons revealed that the main effect of trial type was driven by potentiation of startle responses elicited during CS+ compared to CS- trials  as well as between CS+ and ITIs .Even though the visual inspection of reinstatement patterns indicated differences between experimental groups  or their interaction  = 2.544, p = 0.079) significantly affected SCR magnitudes. As evident from Fig. ps ≥ 0.530). Thus, to control for these baseline differences, we introduced CS differences during pre-conditioning as a covariate in all subsequent tests on SCR magnitudes during acquisition and extinction training.A linear mixed model testing the fixed affects CS type (CS+ vs. CS−) and instruction group revealed that during acquisition training revealed that SCR magnitudes generally decreased  = 17.549, p < 0.001, partial R² = 0.248), but CS+ presentations elicited increased SCR magnitudes compared to CS- presentation  = 31.291, p < 0.001, partial R² = 0.104) and this differentiation developed with increasing training trials  = 2.170, p = 0.014, partial R² = 0.031). SCRs during acquisition training were not significantly influenced by the instruction group  = 2.723, p = 0.067) nor, more importantly, by any interaction between groups and other fixed effects  when controlling for differential CS responding during pre-conditioning and its association with the experimental groups.A linear mixed model testing the fixed effects CS type, trial number and instruction group during extinction training revealed the SCR magnitudes no longer differed between CS+ and CS− presentations  = 1.731, p = 0.189), but confirmed a main effect of instruction group  = 5.588, p < 0.001, partial R² = 0.019) as well as an interaction between instruction group and extinction trial number  = 2.345, p < 0.001, partial R² = 0.003) when controlling for SCR baseline effects. Following up on this interaction with ANOVAs with the fixed effect trial number conducted separately for each instruction groups revealed that SCRs significantly changed during the course of extinction training in the UE group  = 8.465, p < 0.001, partial R² = 0.216), but not in the instructed groups . Bayesian ANOVAs with the repeated measure trial number revealed Bayes factors of 0.00 for both the VIE and VIE+ R group, thus, conforming the null hypothesis that SCR magnitudes did not differ between extinction trials.A linear mixed model testing the fixed effects CS type, trial number and instruction group during F = 8.726, p < 0.001, partial R² = 0.346), but no main effect of CS type or their interaction . Sidak-corrected pairwise comparisons revealed that SCRs during the first extinction trial of both CS types were higher in the UE group than in the VIE  and the VIE+ R group  with no difference between instructed groups . A Bayesian ANOVA revealed a Bayes factor of 0.10, i.e. supporting the hypothesis that SCRs during the first extinction trials did not differ between VIE and VIE+ R groups.Additionally, we investigated immediate extinction effects by testing the fixed effects CS type and instruction group for the first extinction trial only. Here, we found a large main effect of instruction group . Bayesian one-way ANOVAs with the repeated measure CS type revealed Bayes factors of 0.17 (UE), 0.22 (VIE) and 0.14 (VIE+ R) which confirmed a complete extinction of conditioned SCRs in all experimental groups as a baseline for return of fear tests on day 2.During the last two trials of extinction training neither CS type nor instruction group or their interaction significantly affected SCR magnitude  = 159.285, p < 0.001, partial R² = 0.263) and varied between instruction groups  = 5.124, p = 0.006, partial R² = 0.062). Separate tests for the two re-exposure phases revealed no effect of CS type during re-exposure without the US electrode  which was confirmed by a corresponding Bayes factor of 0.09, but a significant increase of SCRs during CS+ compared to CS- presentations after reattachment of the US electrode  = 5.884, p = 0.016, partial R² = 0.030). In addition, the main model revealed a significant interaction between instruction group and reattachment of the US electrode  = 3.667, p = 0.026, partial R² = 0.006). Follow-up univariate analyses of variance conducted separately for the instruction groups revealed the largest increase of SCRs in the VIE group  = 78,649, p < 0.001, partial R² = 0.305), followed by the UE  = 55.458, p < 0.001, partial R² = 0.201) and then the VIE-R group  = 38.632, p < 0.001, partial R² = 0.148).During re-exposure to the CSs after 24 hours, SCRs were strongly increased by the reattachment of the US electrode .To test for baseline differences in CS valence ratings, we conducted a linear mixed model with the fixed effects of CS type and instructions group on ratings obtained after the F = 94.017, p < 0.001, partial R² = 0.536; i.e., more negative judgments for the CS+), time of query  = 14.006, p < 0.001, partial R² = 0.080; i.e., generally less negative judgments after extinction than after acquisition training), as well as their interaction  = 7.878, p = 0.005, partial R² = 0.045). However, we did not observe any main effect of or interaction with the instruction group , see Fig. To test for learning effects on day 1, we conducted a linear mixed model with the fixed effects CS type, time of query (assessment after acquisition training vs. assessment after extinction training) and instruction group. We found significant main effects of CS type . Using Bayesian tests for independent samples to compare differential valence judgments after extinction training in the UE group with the instructed groups, however, revealed Bayes factors of 2.56 (UE vs. VIE) and 2.33 (UE vs. VIE+ R), thus, provided no support for the hypothesis that valence judgments did not differ between groups after extinction training. Moreover, Bayesian one-way ANOVAs with the repeated measure CS type revealed Bayes factors of 28.72 in the UE group, thus, strong evidence for differential CS valence judgments after extinction training, of 3.58 in the VIE group, thus, moderate evidence for differential judgments, and of 2.99 in the VIE-R group, thus, limited support for differential judgments. To control for possible group differences in differential valence judgments after extinction training, we therefore introduced CS differences after extinction training as a covariate in subsequent tests on CS valence on day 2.To ensure a comparable baseline for return of fear tests on day 2 in view of the visible differences between groups in Fig. In the present study, we tested the effect of instructions given prior to extinction training that no further US will be applied with or without corresponding removal of the US electrode on extinction learning and return of fear. We found that instructions were associated with an immediate extinction of conditioning SCRs irrespective of US electrode removal and facilitated the extinction of conditioning startle blink responses. During re-exposure to the CSs 24 h later, we observed no effect of instructions on the recovery of conditioned startle blink responses and CS valence ratings. After reattachment of the US electrode, the increase in SCRs differed between instruction groups with the largest effect in verbally instructed participants. The presentation of an unsignaled US resulted in a general increase in startle blink magnitudes, but we observed neither a reinstatement of differential startle or SC responding to subsequent CS trials nor any interaction with instructions groups.12 whether the US electrode is removed or not13. Thus, instructions seem to override cognitive relational learning as indicated by conditioned SCRs21 by immediately establishing a CS-noUS association. This interpretation is further supported by corresponding earlier findings on the immediate extinction of differential US expectancy ratings by way of instructions11. The UE group also showed an immediate loss of differential CS responses but caused by a pronounced increase of CS- responses  and no information for a second CS+ and found that instructions facilitated extinction learning. If instructions were not repeated, however, they observed no difference between the informed and the uninformed CS+ during extinction recall. Similarly, we observed no significant interaction between instruction group and CS type in our data during the extinction recall test in a threatening context (RE2). Here, only the general increase in SCRs in the threatening context was most pronounced in participants who were instructed about the subsequent absence of US applications prior to extinction training indicating that verbal instructions may actually decrease the strength of declarative CS-noUS associations formed during extinction training31. Alternatively, instructions may serve as a cognitive context for extinction learning25 on the first day and, thus, the lack of instructions on the second day may impair the recall of context-dependent extinction memories29. However, these findings are at odds with a recent report of less return of fear assessed with US-expectancy ratings in participants who were instructed prior to extinction training that the probability of US application would be extremely small in the remainder of the experiment32. Future research should therefore attempt to replicate the observed effect on the recovery of differential SCRs under threat before assuming a meaningful association between verbal instructions and extinction memory.In a recent study, Javanbakht and coworkers24, we did not observe any effects of instructions given prior to extinction training on the reinstatement of conditioned responses by an unsignaled US presentation. According to the retrieval model29, re-exposure to the US evokes a newly formed excitatory association between the US and the context which elicits the retrieval of the latent conditioned CS-US association over the competing inhibitory CS-noUS association. Thus, our results further support the assumption that instructions do not influence the strength of extinction memories.Replicating previous findings33. Another limitation of this study concerns the assessment of CS valence only after, but not during the experimental phases. Online ratings allow to capture immediate instruction effects and, thus, are especially preferable in this line of research9. At least on day 1, however, ratings after each of the experimental phases should have prevented any interference34 or renewal9 effects and, thus, ensured the general interpretability of the reported CS valence ratings. Finally, differential interpretations of FPSs and SCRs in the context of fear conditioning research must take into account that these two outcome measures are evoked under systematically different conditions, SCRs by the cue onset and FPSs by an additional probe, temporally much closer to a possibly occuring US. That is, instead of tapping into different memory systems, differential findings for both measures might be due to other factors such as threat imminence35 which should be systematically explored in future research.Our findings regarding the reinstatement of fear, however, must be interpreted with caution. The incomplete re-extinction of conditioned fear after reattachment of the US electrode may have prevented both the observation of reinstatement main effects as well as effects of instructions given prior to extinction training7, our results correspond with meta-analytic clinical evidence that cognitive behavioral and exposure only treatments for anxiety disorders are equally effective36. However, it has been shown that contingency information facilitates extinction recall when provided again directly prior to return of fear tests25. Moreover, effects of instructions on fear expression and extinction learning vary with characteristics of the participants8. Thus, future research may investigate how these procedural and individual characteristics mediate the effect of instructions on return of fear and may provide a point of reference for individualized treatments.In conclusion, instructions about the subsequent absence of US stimulation given prior to extinction training substantially influence conditioned responding during extinction training, but hardly have any effect on the return of fear assessed 24 hours later under various conditions. That implies that inhibitory CS-noUS associations may be established faster when extinction training is instructed, but inhibitory extinction memories formed after corresponding instructions are not necessarily stronger in the long term. Since return of fear tests are considered a laboratory analogue to relapse and the stability of improvements after exposure treatment of anxiety disorderset al.37. Participants were 126 students of the University of Greifswald between the ages of 18 and 35 who were selected based on a telephone interview in which we checked for the following exclusion criteria: impaired hearing or color vision, excessive smoking habits (>10 cigarettes a day), competitive athletes, self-reported diagnosis of a neurological or mental disorder, regular intake of medication that affects the cardiovascular or central nervous system, neurodermatitis and pregnancy. Participants were randomly assigned to one of the three experimental groups stratified by gender and age. All participants gave written informed consent to the experiment approved of by the ethics committee of the University of Greifswald and performed in accordance with the Declaration of Helsinki.This investigation is part of a larger project, thus, details about the sample have already been provided in Wendt N = 120 with n = 40 per experimental group. As targeted, gender distribution  = 0.200, p = 0.905) and average age  = 0.78, p = 0.461) did not differ significantly between groups. On day 2, the experiment was terminated prematurely for eight participants at their own request or due to technical difficulties (each 2 from the UE and VEI group and 4 from the VEI + R group) leaving a sample of N = 112 for the second day of measurement, again without significant differences in gender (Χ² < 1) or age (F < 1) distribution. Analyzed samples can differ dependent on the outcome measures and are reported in the corresponding sections.The experiment was prematurely terminated for six participants on day 1 either due to technical difficulties or at their own request leaving a sample of 38 served as CSs and were presented for seven seconds. Two different orders mirrored each other with regard to CS+ and CS− presentations to account for initial sensitization and subsequent habituation effects and were balanced between participants. CS+ and CS− presentations were pseudo-randomized with no more than two consecutive presentations of the same condition. Assignment of each the faces as threat (CS+) or safety (CS-) signal was also balanced between participants. The US was a 10 ms train of 500 Hz single electrical pulses , applied to the participants’ left ankle, adjusted for each participant individually to a level that was “highly unpleasant, but not painful” and presented 6.95 sec after onset of the CS+. The mean physical intensity of the US was 21.78 mA (SD = 20.80) and did not differ significantly between the three groups  = 1.244, p = 0.292). The acoustic startle probe was a 95 dB(A) white noise, presented 5.5 or 6.5 sec after cue onset and 11, 12 or 13 sec after cue offset during inter-trial intervals (ITIs) for 50 ms. The duration of ITIs, during which a fixation cross was presented, varied between 11 and 18 sec. The presentation of visual stimuli was controlled by Presentation (version 17), presentations of startle probes and USs by VPM39.The differential cue conditioning paradigm spanned two sessions on consecutive days, approximately 24 hours apart (tolerance range ± 2 hours). On day 1, participants took part in a fear acquisition and extinction training, and on day 2, we tested for spontaneous recovery and reinstatement of fear as described below . Then, four startle probes were presented without visual foreground stimuli to account for startle habituation effects (habituation 1), followed by a pre-conditioning phase in which startle probes were administered during four presentations of each of the CS and additionally four times during the ITIs. Afterwards, participants rated the valence and arousal of each of the CS as well as the startle probe to determine a baseline liking of the CS. Then the US electrode was attached and the US intensity was individually adjusted. Participants were informed that all stimuli  would be presented in the following experimental phase and that they have no special task other than keeping their eyes open and focusing on the screen. The acquisition training was preceded by four startle probes presented without visual foreground stimuli to account for sensitization effects due to the US work-up procedure (habituation 2). During the acquisition training 9 out of 12 CS+ trials were reinforced by US presentations, while 12 CS- trials never included US presentations. Then the examiner entered the room, valence and arousal ratings were obtained for each of the CSs as well as for the startle probe and the US and participants were instructed according to their group assignment. Participants of the UE group were told that the experiment will continue after a short break and both participants of the VIE and the VIE-R group were instructed that no further US will be applied. In the VIE-R group the US electrode was additionally removed which was accompanied by an explicit statement that the US electrode is now removed. During the subsequent extinction phase, CS+ and CS− were presented 12 times each with no further US presentations. Startle probes were administered during all CS+ and CS− presentations as well as during a corresponding number of ITIs, i.e., each 12 during the acquisition and the extinction training. Afterwards, valence and arousal ratings were obtained again, participants were interviewed to determine their awareness of CS-US contingencies. Overall, 11.67% of the participants were unaware of CS-US contingencies and the proportion of unaware participants did not differ between extinction groups (Χ²(2) = 2.102, exact p = 0.455).Upon arrival in the laboratory, participants were informed about materials and procedures and signed a corresponding consent form. Afterwards the sensors for physiological data recording were attached and an electrocardiogram (ECG) was recorded for six minutes to determine resting heart rate variability 41, the List of Threatening Experiences (LTE)42 and the Resilience Scale (RS-11)43. Trait anxiety  = 0.22, p = 0.805), childhood adversity  = 1.36, p = 0.261), number of threatening experiences in the last twelve months  = 0.00, p = 0.999) and resilience subsumed as coping with change or misfortune  = 0.51, p = 0.603) did not differ significantly between groups.The second session began 24 ± 2 hours after the first with another six minute resting period for ECG recording after the sensors for physiological data recording were reattached. After four presentations of startle probes without visual foreground stimuli to account for startle habituation effects, spontaneous recovery of the CR while the US electrode was not attached (re-exposure 1), participants were re-exposed to each four CS+ and CS− presentations. Startle probes were presented in all CS and in four ITI trials. Then, valence and arousal ratings were obtained, the US electrode was reattached and participants were informed that all stimuli experienced the day before could be presented in the following experimental phases. To test for spontaneous recovery of the CR while the US electrode was attached (re-exposure 2), participants were again re-exposed to each four CS+ and CS− presentations and startle probes were presented in all CS and in four ITI trials. Afterwards one unsignaled US presentation during an ITI was used to test the reinstatement of fear by re-exposure to the aversive event. Whether that ITI was preceded and followed by CS+ or CS- trials was balanced between participants. Startle probes were presented in all 12 CS+ and 12 CS- trials that followed and additionally 12 times during the ITIs. No further US were applied during the final experimental phase. Then valence and arousal ratings were obtained again and participants completed a set of questionnaires including German versions of the State Trait Anxiety Inventory (STAI)Electromyographic (EMG) activity was recorded over the left orbicularis oculi muscle to measure the eyeblink component of the startle response using two Ag/AgCl miniature surface electrodes  filled with electrolyte (Marquette Hellige). A Coulbourn S75-01 bioamplifier served to amplify the raw EMG with a 30 Hz high-pass filter and a 400 Hz Kemo-VBF8-03 low-pass filter. Digital sampling was set to 1000 Hz from 100 ms prior to until 400 ms after onset of the startle probe. The EMG signal was digitally filtered offline through a 60 Hz high-pass filter and was rectified and integrated (time constant: 10 ms).44 that automatically identified latency of blink onset and peak amplitude in microvolts. All trials were visually inspected and trials with no detectable blinks were scored as zero responses, trials with excessive baseline activity or recording artefacts as missing . To reduce the influence of individual differences unrelated to the research question, blink magnitudes were standardized for each participant using a z-score transformation with all blinks from both days as a reference distribution45. The standardized responses of each participant were then converted to T scores [50 + (z × 10)].Startle blink responses were defined when starting 20–120 ms after probe onset and peaking within 150 ms using a custom made computer algorithm42 of >50% .Due to technical difficulties during EMG measurement, FPS data from nine (day 1) resp. 11 (day 2) participants were excluded from analysis. Another two (day 1) resp. one (day 2) participant(s) were excluded from analysis because they failed to reach a startle probability (1 - (N zero responses/(N probes - N missings))44.Electrodermal activity (EDA) was recorded from the hypothenar eminence of the palmar surface of the participant’s right hand. A Coulbourn S71-22 skin conductance coupler provided a constant 0.5 V across two Ag/AgCl standard electrodes  filled with a 0.05 M sodium chloride electrolyte medium. The analog signal was sampled continuously at a rate of 10 Hz. SCRs were scored from trough-to-peak as the first increase starting between 0.9 and 4.0 s after cue onset  and within the presentation of the CSs (7 s) to avoid confounding with SCRs to the USs, again using a custom made computer algorithmN = 108, analyzed sample day 2 N = 102). SCRs were square-root-transformed to compensate for skewed distributions and range-corrected based on the maximum SCR (including both CRs and URs) prior to statistical analyses.Due to technical difficulties during EDA measurement, data from nine (day 1) resp. seven (day 2) participants were missing for SCR analysis. Another three participants were defined as SCR non-responder because they showed no increase in skin conductance in response to more than 50% of US presentations and excluded from all further analysis  and two times on day two . Ratings were acquired from 1  to 9 (very unpleasant/arousing) using the Self-Assessment Manikin Scale (SAM)All measures were checked for baseline group differences which were then entered as covariates in the corresponding analyses if appropriate. Responses during pre-conditioning served as baseline for the analyses of the acquisition and extinction phases on day 1, responses during the last two trials of extinction training as baseline for the analyses of the re-exposure phases on day 2.47. In case of significant main effects and more than two factor levels, Sidak-corrected pairwise comparisons are reported along with 95% confidence intervals. In case of significant interactions, follow-up linear mixed models were used to explore their nature. In case of non-significant effects, Bayes factors were calculated as implemented in Version 25 of IBM SPSS Statistics to determine the likelihood of the data under the null hypothesis of no effect and Bayes factors lower than 1/3 were considered as support for the null model48.Startle blink magnitudes were analyzed using linear mixed models as implemented in IBM SPSS Statistics (Version 22) with the repeated covariance structure set to AR1 (autocorrelated) to account for expected timing-dependent differences in correlations between observations in this learning paradigm. Partial R² was calculated for significant effects as a measure of effect size for fixed effects33, the repeated covariance structure was set to compound symmetry here.To test for baseline differences between groups, startle blink magnitudes during pre-conditioning were tested for the fixed effects trial type (CS+ vs. CS- vs. ITI) and instruction group (VIE vs. VIE+ R vs. UE). To account for learning affects during acquisition and extinction training, trial number  introduced as fixed effects as well as trial type and instruction group into the respective models. To test for immediate extinction effects, a separate analysis was run testing the fixed effects trial type and instruction group on the first extinction trial only. The model for return of fear on day 2 included the fixed effects trial type, US electrode reattachment (pre vs. post) and instruction group. Reinstatement effects were tested with a model that included the fixed effects trial type, reinstatement US  and instruction group. Since only one trial per condition was included in the reinstatement modelSCRs were analyzed as described for startle blink magnitudes except that the three-level factor trial type was replaced by the two-level factor CS type (CS+ vs. CS-) since no SCRs were obtained during ITIs. CS valence ratings were analyzed in three linear mixed models with the repeated covariance structure set to compound symmetry: The first one to check for baseline differences during pre-conditioning with CS type and instruction group introduced as fixed effects, the second model was used to test learning effects on day 1 with the fixed effects CS type, time of query (assessment after acquisition training vs. after extinction training) and instruction group and the third model to test for return of fear on day 2 with the fixed effects CS type, time of query (assessment after re-exposure 1 vs. after completion of the experiment) and instruction group.


Coarctation patients before curative reconstruction are exposed to abnormal flow patterns which potentially could cause wall deterioration. This study evaluated the effect of age at correction on the pulse wave velocity (PWV) and peak wall shear stress (WSS) in adolescent patients with corrected coarctation. Effects of valve morphology and presence of reobstruction were also evaluated.n = 14; reobstruction, n = 9). Mean age at correction was 1.0 ± 1.8 years. PWV was determined from two high-temporal through-plane phase-contrast magnetic resonance imaging (MRI) acquisitions, for two segments: ascending aorta plus aortic arch and descending aorta. WSS was determined from four-dimensional flow MRI. Peak WSS over five systolic phases was determined for ascending aorta, aortic arch, and descending aorta.Twenty-one patients aged 13.7 ± 2.6 years (mean ± standard deviation) were included . Significant differences were found between patients without and with reobstruction for peak WSS in the aortic arch  and descending aorta .Patients with tricuspid aortic valve showed a significant correlation between the age at correction and descending aorta PWV (A prolonged period of abnormal haemodynamic exposure may result in increased aortic wall stiffening. The increased peak WSS as results of a reobstruction possibly promotes different disease progression, which endorse longitudinal follow-up examination of corrected coarctation patients. Coarctation correction age correlates with descending aorta pulse wave velocity in patients with tricuspid aortic valve.Recurrent obstruction induces higher peak wall shear stress in the aortic arch.Recurrent obstruction induces higher peak wall shear stress in the descending aorta.Aortic coarctation (CoA) is a congenital obstruction of aorta –3, typic. The viscous friction of the blood  on the vessel wall regulates the endothelium lining properties, which by high wall shear stress (WSS) promotes vascular dilatation and remodelling [Before reconstruction, the local aortic narrowing results in an increased afterload of the heart and a pressure gradient over the obstruction with associated formation of abnormal aorta flow patterns . The visodelling . Additioodelling . It is uodelling . Knowledodelling . Paradoxodelling  but alsoodelling . Howeverodelling .In the literature, phase-contrast magnetic resonance imaging (MRI), also known as velocity-encoded or flow MRI, has been applied as innovative application to analyse aortic flow haemodynamics in healthy controls and patients. For example, within CoA patients, flow MRI is utilised to examine the pulse wave velocity (PWV), a surrogate marker for the aortic wall stiffness, and WSS. These studies –19 demonTherefore, this study was aimed at evaluating the effect of age at curative reconstruction on the aortic wall stiffness expressed as PWV and the haemodynamic load expressed as peak WSS in adolescent patients with corrected CoA. Also, effects of valve morphology and presence of reobstruction were evaluated. Our hypothesis is that a correction for CoA patients at younger age may result in less aortic wall stiffening and lower peak haemodynamic load, as a result of the shorter period of hypertension in the arterial system upstream of the coarctation site and exposure to abnormal flow patterns distal to the obstruction.e.g., patient movement and endurance) during the MRI. The included 21 patients were aged 13.7 ± 2.6 years (mean ± standard deviation), including 12 patients with bicuspid aortic valve (BAV) and 9 patients with tricuspid aortic valve (TAV). Mean age at CoA correction was 1.0 ± 1.8 years, performed by end-to-end anastomosis in 16, extended end-to-end anastomosis in 2, and subclavian flap in 1 patient. Only one patient, as result of a recurrent obstruction, underwent a reoperation using an autologous pericardial patch. None of the patients had a clinical indication for reintervention at the time of the MRI examination. The included patients were scanned between September 2015 and May 2016, and time between reconstruction and MRI was 12.6 ± 3.0 years.This prospective study protocol was approved by the Medical Ethics Committee of the Leiden University Medical Center (P14.095), and informed consent was signed by both parents/guardians of all subjects. Children with chromosomal disorder were excluded to preserve homogeneity of the population. Thirty-two patients after surgical CoA repair participated in the study and underwent a cardiovascular magnetic resonance imaging (MRI) examination. These patients were also included in a previous study with the aim to investigate the cardiac autonomic nervous system activity, cardiac function, and their relationship in children after CoA repair . EventuaThe presence of an aortic reobstruction was determined based on the maximal flow velocity in the descending aorta, measured by a suprasternal transthoracic Doppler echocardiogram  by a single observer (IN), supervised by an experienced clinician (AH) in all patients. The acquired images were stored and analysed offline using the EchoPAC software version 113 . Based on this analysis, the presence of a reobstruction was determined, defined as a maximal flow velocity larger than 2.5 m/s . Using tThe image acquisition consisted of two MRI through-plane phase-contrast MRI sequences to determine aortic PWV and one four-dimensional (4D) flow MRI sequence. MRI for all patients were performed on a 3-T scanner  using a combination of both a FlexCoverage posterior coil in the table and a dStream Torso anterior coil, together providing up to 32-coil elements for signal reception. Concomitant gradient correction and local phase correction were performed from standard available scanner software.The PWV was determined from high-temporal through-plane phase-contrast MRI using free breathing with retrospective electrocardiographic gating, for both the proximal aorta (ascending aorta plus aortic arch) and the descending aorta. This was accomplished by measuring the flow velocity through two planes positioned perpendicular to aortic centreline: the first plane intersecting both the ascending and thoracic descending aorta and the second plane intersecting the abdominal descending aorta, defined as proximal PWV and diaphragmatic PWV, respectively. The proximal PWV MRI sequence parameters were as follows: velocity encoding of 200–300 cm/s in feet-head direction, acquired temporal resolution 8.4 ms, reconstructed temporal resolution 4.1 ms (171 ± 24 phases), echo time 2.3 ms, repetition time 4.2 ms, flip angle 20°, field of view 350 × 350 × 8 mm, and acquired spatial resolution 2.8 × 2.8 × 8.0 mm. Acquisition time and heart rate were on average 75 ± 10 s and 83 ± 12 beats per min, respectively. Diaphragmatic PWV MRI sequence parameters were as follows: velocity encoding of 150–250 cm/s in feet-head direction, acquired temporal resolution 8.6 ms, reconstructed temporal resolution 4.1 ms (167 ± 23 phases), echo time 2.4 ms, repetition time 4.3 ms, flip angle 20°, field of view 350 × 350 × 8 mm, and acquired spatial resolution 2.8 × 2.8 × 8.0 mm. Acquisition time and heart rate were on average 78 ± 12 s and 84 ± 11 beats per min, respectively.The aortic 4D flow MRI sequence used a hemidiaphragm respiratory navigator, a retrospective ECG gating, and a standard non-symmetrical four-point velocity encoding. Sequence parameters were as follows: velocity encoding of 200–350 cm/s in four directions, acquired temporal resolution 34.4 ms, reconstructed temporal resolution 29.2 ms (26 ± 4 phases), echo time 2.4 ms, repetition time 4.3 ms, flip angle 10°, field of view 350 × 350 × 52.5–72.5 mm, acquired spatial resolution 2.5 × 2.5 × 2.5 mm, segmentation factor 2, and sensitivity encoding factor 2 in anterior-posterior direction. Acquisition time was on average 4.9 ± 0.7 min excluding the respiratory compensation. Due to the acceptance window of the respiratory navigator, the actual acquisition time in the scanner approximately doubled.The image analysis consisted of two parts to determine aortic PWV and the WSS. In order to obtain the PWV, the acquired proximal PWV and diaphragmatic PWV images firstly were analysed using the in-house developed software MASS (LUMC). This software was used to perform velocity mapping and to measure the length of both aortic segments on a multislice survey of the aorta. Lastly, these quantifications were imported into an in-house developed MATLAB-based application to determine the PWV of the proximal and descending aorta, using the foot-to-foot method Fig. . In all e.g., the subclavian and carotid arteries). Secondly, the anatomical segmentation planes were manually placed and imported perpendicular to the aortic wall. From proximally to distally on the aorta, these planes were positioned at the aortic valve, proximally against the brachiocephalic artery, distally against the subclavian artery, and 10 cm caudal below the diaphragm. Thirdly, for the five available time phases and each anatomical segment, the maximal WSS was exported from CAAS. Lastly, these maxima over the five time phases were used to determine the peak WSS for each anatomical segment over all five time phases. The WSS image analysis was performed by a single observer (IN) in all patients. The applied method to determine the WSS in the five systolic time phases was previously described and validated on the reproducibility by van der Palen et al. [From 4D flow MRI, the WSS was determined using CAAS MR Solutions v5.0 , assuming a constant blood viscosity of 4 mPa s. This software was used to compute the WSS over five time phases and three consecutive aortic segments Fig. : the aorn et al. .t test or Mann-Whitney U test, respectively used for parametric scale data or non-parametric scale and ordinal data. Correlations between variables within groups were evaluated using the Pearson (rP) and Spearman rank (rS) correlations, respectively used for parametric scale data or non-parametric scale and ordinal data. The Levene test was used to verify the equality of variance and Shapiro-Wilk test to verify the normality of the data. The absolute correlation coefficient (rP or rs) was classified as follows: 0.30 < |r| < 0.50, weak; 0.50 < |r| < 0.70, moderate; 0.70 < |r| < 0.85, good; and |r| > 0.85, strong. All statistical tests were two-tailed, and a p value of less than 0.05 was considered significant. Data will be presented as mean values with standard deviations.The statistical analysis was performed using the SPSS v23 software . Differences between groups were compared using the independent sample n = 21) were found between the following parameters: the age at correction and MRI, PWV in the proximal and descending aorta, PWV ratio, and peak WSS in the ascending aorta, aortic arch, and descending aorta. And, for the same parameters, non-significant group differences between the BAV and TAV subgroups were found . For patients with a TAV, a significant good correlation was found between age at correction and descending aorta PWV , significant differences were found for the peak WSS in the aortic arch  and descending aorta , indicating higher peak WSS values for patients with a reobstruction proximally and distally to the lesion. The statistical analysis within subgroups subdivided on both the aortic valve morphology and the presence of reobstruction was not performed, due to small population sizes within these subgroups. Examples of three-dimensional magnitude WSS maps of patients, subdivided on the aortic valve morphology and the presence of reobstruction, are shown in Fig. Characteristics of the CoA patients and subgroups are shown in Table In this study, the effect of age at curative reconstruction on the aortic wall stiffness expressed as PWV and the haemodynamic load by viscous friction on the arterial wall, expressed in peak WSS, was evaluated in adolescent patients with corrected CoA. Also, the effects of the aortic valve morphology and presence of reobstruction were evaluated. The main findings of this study were as follows: (1) a significant positive correlation between age at correction and PWV in the descending aorta for the TAV subgroup and (2) a significant difference in peak WSS in the aortic arch and descending aorta between the subgroup without reobstruction and the subgroup with reobstruction.r = 0.33) between the age at correction and the descending aorta PWV within their entire patient group, incorporating 16 BAV and 35 TAV patients. This effect presumably may be influenced by substantial larger group of TAV patients compared to BAV patients. Unfortunately, these authors did not statistically analyse this correlation separately within both aortic valve morphology subgroups.The observed positive correlation for TAV subgroup between the age at correction and descending aorta PWV suggests that a prolonged period of abnormal haemodynamic exposure may result in increased aortic wall stiffening. Specifically for TAV patients, this is in line with the hypothesis that for CoA patients, a curative reconstruction at a younger age will result in less wall stiffening, thus a lower PWV. This result should be interpreted with caution, since no correlation was found within the entire patient group nor in the BAV subgroup. The absence of a comparable correlation for these groups may be explained by the abnormal haemodynamics of BAV patients , potentiThe observed peak WSS differences in the aortic arch and descending aorta between the patients without and with reobstruction imply that local luminal narrowing results in an increased haemodynamic load on the aortic wall proximally and distally to the lesion. This effect was predominant within the aortic arch. Multiple studies indicated that endothelium lining properties are highly sensitive to the applied WSS on the vessel wall, which promotes adaptive dilation or structural remodelling of the artery wall during high WSS . TherefoThe present study has several limitations. Firstly, the number of CoA patients was limited by the available data, resulting in a relatively small population size and statistical power which also made the comparison of subgroups based on multiple patient characteristics difficult. Still, we were able to detect statistical significant findings for these limited group sizes. Secondly, the study only incorporated patients and no healthy controls, excluding the possibility to compare our results with reference values. Thirdly, the single-centre design limited the patient diversity, resulting in a relatively small variation of age at CoA correction. Fourthly, the severity of CoA prior to reconstruction is an important confounder. However, information of the severity of CoA was not available and therefore not involved in the statistical evaluation.In conclusion, the association between the age at correction and descending aorta PWV for TAV patients suggests that a prolonged period of abnormal haemodynamic exposure may result in increased aortic wall stiffening. The increased peak WSS as results of a reobstruction possibly promotes different disease progression, which endorse longitudinal follow-up examination of corrected CoA patients.


CAD) remains to be elucidated. The present study aimed to investigate the association of serum Metrnl with CAD in Chinese patients. A total of 193 patients with CAD and 156 control subjects were enrolled in this study. Serum Metrnl concentration was measured by enzyme‐linked immunosorbent assay. Anthropometric phenotypes, fasting glucose, serum lipids, and inflammatory cytokines were measured. Serum Metrnl was lower in CAD patients when compared to those controls . Serum Metrnl was negatively correlated with metabolic parameters, including body mass index, total cholesterol, and low‐density lipoprotein cholesterol as well as inflammatory markers including high‐sensitivity C‐reactive protein, IL‐1β, and IL‐11 even after adjustment for potential confounding variables (P < 0.05). In multivariable logistic regression analyses, compared to those in the highest tertile of serum Metrnl levels, subjects in the lowest tertile had the highest risks for CAD . After adjustment for potential confounding variables, serum Metrnl was also decreased as the number of stenosed vessels increased (P < 0.001). Furthermore, decreased Metrnl level was negatively correlated with the severity of CAD quantified by the Gensini score. This first case‐control study shows significant associations of serum Metrnl with the presence and severity of CAD, suggesting Metrnl might be a new promising therapeutic target for CAD.Meteorin‐like (Metrnl) is a novel adipokine that is highly expressed in white adipose tissue. Metrnl stimulates energy expenditure and improves glucose tolerance in rodents. However, whether Metrnl plays a role in coronary artery disease ( The CAD patients were recruited from inpatients admitted to the Affiliated Sir Run Run Hospital and Second Affiliated Hospital of Nanjing Medical University because of angina pectoris or other symptoms or signs of cardiovascular disease. Acute myocardial infarction (AMI) was diagnosed if a patient had a cardiac troponin I level exceeding the 99th percentile of a normal reference population with ≥1 of the following: chest pain lasting >20 minutes, diagnostic serial electrocardiographic changes consisting of new pathologic Q waves, or ST‐segment and T‐wave changes.2.2Two cardiologists who were unaware of the patients included in this study assessed the angiograms. CAD was defined as luminal diameter narrowing estimated visually at least 50% in any epicardial coronary artery, including the left main coronary artery, left anterior descending, left circumflex, or right coronary artery. CAD patients were divided into single‐, double‐, and triple‐vessel disease subgroups according to the number of significantly stenosed vessels. The severity of CAD was assessed with the Gensini score system based on the degree of luminal narrowing and its geographic importance.2.3g for 10 minutes. The supernatant (serum) was collected and further centrifuged at 10 000 g for 15 minutes to completely remove the cell debris. The obtained serum was stored at −80°C before further analysis. Total cholesterol (TC), triglyceride (TG), high‐density lipoprotein cholesterol (HDL‐C), and low‐density lipoprotein cholesterol (LDL‐C) levels were measured enzymatically on a chemistry analyzer . Glucose levels were measured by a glucose oxidase method . High‐sensitivity C‐reactive protein (hs‐CRP) was determined using an enzyme‐linked immunosorbent assay kit .Venous blood sample was collected from each subject. The whole blood was separated into serum and cellular fractions within 2 hours by centrifugation at 3000 2.4Inflammatory cytokines including IL‐1β, IL‐8, and IL‐11 were measured using the CBA Human Soluble Protein Detection Kit  as previously described.2.5Serum Metrnl levels were measured by using an enzyme‐linked immunosorbent assay kit (R&D systems) according to the manufacturer's protocol. The intra‐ and interassay coefficients of variance were 2.59% and 3.55% respectively. The analytic sensitivity of the assays was 15.625 ng/mL.2.6t test. Skewed data, including SBP, DBP, TC, TG, HDL‐C, FBG, Cr, hs‐CRP, IL‐1β, IL‐8, IL‐11, Gensini score, and Metrnl, were expressed as median and quartile ranges, and comparisons were analysed by the Mann‐Whitney U test. Pearson chi‐squared test was used to compare qualitative variables represented as frequencies. The correlations between serum level of Metrnl and other variables were calculated using Spearman correlation coefficient and partial correlation coefficient adjusted for age, sex, smoking, alcohol intake, BMI, Cr, FBG, TC, TG, and LDL‐C, as appropriate. Univariate analysis and multivariate logistic regression analysis were taken to determine the variables that independently contributed to the presence of CAD. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Linear regression analysis was used to test for trend of the changes of serum Metrnl concentrations across the severity of coronary angiography . Receiver operating characteristic (ROC) curve analysis was used to determine the optimum cut‐off level of Metrnl best predicting CAD. To assess the performance of predictive model of Metrnl for CAD, we calculated the concordance (c) statistics for discriminative ability and goodness of fit statistics for calibration. All tests were two‐sided and P < 0.05 was considered statistically significant.Statistical analyses were performed using PASW 18.0 . Normality of distribution was assessed using the Kolmogorov‐Smirnov test. Data for age and LDL‐C were normally distributed parameters and presented as the mean ± SD, and comparisons were analysed by Student's P‐values. It was assumed that subjects unexposed to the traditional risk factors and with a Metrnl concentration above the cut‐off value have a certain background risk for CAD . OR01 refers to the relative risk for CAD among those unexposed to a risk factor with a Metrnl concentration below the cut‐off value when compared with those with neither a Metrnl concentration below the cut‐off nor exposure to risk factors. OR10 refers to the relative risk for CAD among those with a Metrnl concentration above the cut‐off value but exposure to an environmental risk factor when compared with those with neither a Metrnl concentration below the cut‐off value nor exposure to risk factors. OR11 is the ratio of the CAD risk among subjects exposed to risk factors with a Metrnl concentration below the cut‐off value when compared with the CAD risk among unexposed subjects with a Metrnl concentration above the cut‐off value. These ORs were used in the calculation of the synergy indexes (SIs), such that SI = (OR11‐1)/(OR10 + OR01‐2) and SIM = OR11/(OR10 × OR01); the relative excess risk due to interaction, RERI = OR11‐OR10‐OR01 + 1; and the attributable proportion of the disease due to interaction, AP = RERI/OR11.To further explore the synergistic effect of Metrnl and classical risk factors on the risk of CAD, a 4 × 2 table approach was conducted to calculate OR, respective 95% CI, and two‐tailed 33.1P < 0.01); higher levels of TG and LDL‐C (P < 0.03); higher levels of FBG, hs‐CRP, and IL‐1β (P < 0.01); higher rates of taking antihypertension drugs, antihyperglycaemic drugs, and hypolipidaemic drugs (P < 0.001); and lower level of IL‐11 (P = 0.005). In addition, the serum levels of Metrnl were lower in CAD patients when compared to the control subjects .Table 3.2r = −0.274; P = 0.001), TC , and LDL‐C  in the CAD group. The correlations remained statistically significant (P < 0.05) after adjustments for age, sex, smoking, alcohol intake, BMI, Cr, FBG, TC, TG, and LDL‐C, as appropriate. Serum Metrnl levels were also negatively associated with BMI , Cr , and LDL‐C  in the control group; however, the correlations lost significance after adjustment for the aforementioned variables. We further investigated the possible interferences of medications with Metrnl levels. Although there was slight increase in serum Metrnl concentrations in patients received antihyperglycaemic therapy, the difference did not reach statistical significance . Similar results were observed in patients received antihypertensive therapy (P = 0.126) and antihyperlipidaemic therapy (P = 0.299).We next investigated the relationship of serum Metrnl levels with various clinical parameters Table . Serum Mr = −0.238; P < 0.001) and IL‐1β , but positively correlated with anti‐inflammatory cytokine IL‐11 . The association of Metrnl with hs‐CRP , IL‐1β , and IL‐11  remained statistically significant even after adjustments for age, sex, smoking, alcohol intake, diabetes, BMI, Cr, FBG, TC, TG, and LDL‐C.We further analysed the relationship between serum Metrnl and inflammatory markers. As shown in Figure 3.3P < 0.01). Finally, we conducted ROC curve analysis to identify the diagnostic accuracy of Metrnl for CAD. The optimal cut‐off value of Metrnl that predicted CAD was 123.5 pg/mL, with a sensitivity of 44.04% and a specificity of 95.51%   is 0.753, indicating good discriminative ability. The calibration curves  also indicate reasonable fit of our model.Univariate and multivariate logistic regression analyses showed that decreased serum Metrnl levels were significantly associated with the presence of CAD both before and after adjustment for potential confounders including age, sex, BMI, smoking, alcohol intake, hypertension, diabetes, hypeylipidaemia, TC, TG, LDL‐C, HDL‐C, FBG, and Cr Table . Similar3.4P = 0.035). Spearman correlation analysis demonstrated negative correlations of Metrnl with the severity of CAD, quantified by the Gensini score   . We further investigated the changes of serum Metrnl in patients with AMI. Interestingly, serum Metrnl levels were also decreased in patients with AMI .We further divided patients with CAD into three subgroups according to the number of stenosed vessels. As the number of affected vessels increased, the Gensini score significantly increased  Figure A. Linear) Figure B. After I Figure C and neg3.5P = 0.081). After exclusion of diabetic patients, subjects in the lowest tertile compared with the highest tertile of serum Metrnl were associated with higher risks for CAD even after adjustment for the potential confounders . Separating subjects into males and females also did not materially change the association of Metrnl with the presence and severity of CAD  or without  diabetes, further clinical studies with larger sample on patients with diabetes are needed to confirm the predictive value of Metrnl for cardiovascular diseases.Metrnl is a novel‐secreted protein homologous to the neurotrophin Metrn.r values in our study, further clinical studies with larger sample are needed to confirm these correlations.Another interesting finding of our study is that serum Metrnl concentrations were independently inversely correlated with metabolic parameters, including BMI, TC, and LDL‐C. It has been long known that metabolic syndrome is associated with increased risk of CAD events.The mechanism underlying the decreased circulating Metrnl in CAD remains unclear. To date, there has been no study that examined the effects of Metrnl in the development of atherosclerosis. Ushach et alOur study should be interpreted within the context of its limitations. The cross‐sectional design does not allow causal inference. Secondly, the relatively small sample size may underpower the results of our study. Thirdly, the CAD patients of our study were actually from a referral population. This might cause the possibility of selection bias and confound the results. In addition, as we only investigated Metrnl levels in Chinese patients, our findings need to be confirmed in other ethnicities.5In summary, our first case‐control study shows significant associations of serum Metrnl with the presence and severity of CAD. Although further prospective and interventional studies are necessary to investigate whether decreased Metrnl may participate in the development of atherosclerosis, our findings provide novel insights into the potential role of Metrnl in CAD.The authors declare that they have no competing interests.Written informed consent was obtained from each participant and this study was approved by the Ethics Committee of the Affiliated Sir Run Run Hospital and Second Affiliated Hospital of Nanjing Medical University.Wei Gao and Xiang Lu designed the study, interpreted the data, and contributed to critically revising the manuscript. Zheng‐Xia Liu, Hui‐Hong Ji, and Min‐Peng Yao completed the project, analysed the data, and wrote the manuscript. Li Wang and Yue Wang contributed to data collection and Metrnl measurement. Xi‐Feng Zheng, Hui‐Wei He, and Lian‐Sheng Wang contributed to recruitment of patients and clinical diagnosis of disease. All authors have approved the final article.DataClick here for additional data file.


Little is known about how different physical activity (PA) parameters relate to cognitive function in older adults. Using accelerometers calibrated to detect vertical impacts from ground reaction forces we examined the associations of low, medium and higher impact PA with processing speed, verbal memory and cognitive state in older adults.n = 558; 48.2% female). Counts of low (0.5 < g < 1.0 g), medium (1 < g < 1.5 g), or higher (≥1.5 g) magnitude impacts were derived from vertical acceleration peaks recorded over 7 days by hip-worn accelerometers. Processing speed was assessed by a timed visual letter search task, verbal memory by a 15-word list learning test and cognitive state by the Addenbrooke’s Cognitive Examination (ACE-III). Potential confounders were childhood cognitive ability, adult socioeconomic position, body mass index and depression.Participants were 69-year old British men and women from the Medical Research Council National Survey of Health and Development included in a vertical impacts and bone sub-study : 0.03 to 0.16), word learning test = 0.05 (95% CI: 0.00 to 0.11), ACE-III scale = 0.09 (95% CI: 0.03 to 0.14). After adjustment for confounders, differences persisted for letter search speed  but were closer to the null for the word learning test  and ACE-III scores . Low impacts remained associated with letter search speed after sensitivity analyses excluding those with functional and musculoskeletal problems, and after adjustment for impacts in higher bands. Modest positive associations between higher magnitude impacts and cognitive test scores were most likely due to chance.Accelerometer-derived low impact physical activity was associated with better visual processing speed in 69-year old men and women independently of childhood cognitive ability and other measured confounders. Day-to-day low impact physical activity may therefore have the potential to benefit cognitive health in older adults.The online version of this article (10.1186/s11556-019-0216-3) contains supplementary material, which is available to authorized users. Evidence suggests that physical activity (PA) improves brain health and can help reduce age-related cognitive decline –3. The iWhereas accelerometer outputs are conventionally classified according to intensity using thresholds calibrated against oxygen consumption, many other characteristics of PA can be evaluated using alternative approaches which can provide novel insights into its relationships to health outcomes. For example, a recent study using a novel and validated method for parameterising older adults’ accelerometer-measured PA according to level of vertical impact , 9 foundTo provide a deeper understanding of the relationship between PA and cognition, in the present study, we aimed to examine the associations between accelerometer-measured PA, classified according to level of vertical impacts, and cognitive performance in a population-based sample of older adults where prior cognitive ability was also assessed prospectively in childhood. We hypothesised that all PA regardless of impact magnitude  would be associated with better cognitive performance and that these associations would be independent of early life cognitive ability.Study participants were from the Medical Research Council (MRC) National Survey of Health and Development (NSHD), a national sample initially consisting of 5362 British births occurring during 1 week in March 1946 that has to date been regularly followed-up to age 69 years . Most paDuring the home visit at age 69, participants were invited to participate in the VIBE study. If they agreed, the nurse provided them with a GCDC X15-1c triaxial accelerometer , custom designed elasticated belt, a time log and a stamped addressed package along with instructions. Accelerometers were configured to a sampling frequency of 50 Hz, a deadband setting of 0.1 g and a timeout setting of 10 s. We instructed participants to wear the accelerometer securely positioned in the belt over their right hip pointing toward the centre of their body for seven continuous days, removing only for sleeping, washing and swimming. Participants were asked to record the times at which the monitor was put on in the morning and taken off at night for each monitoring day and to state reasons, if any, why that day had not been reflective of their normal activity.8. All g values represent above 1 g from earth’s gravitational force.Standardised cleaning and processing of raw accelerometer data was carried out by the study coordinating centre and is described in detail elsewhere . BrieflyCognitive function was assessed at age 69 by tests of processing speed and verbal memory, and by the Addenbrooke’s Cognitive examination-III (ACE-III) scale. Processing speed was assessed by a timed visual search task requiring cancellation of target letters P and W embedded among non-target letters; the speed score was derived from the position reached at the end of 1 minute. Verbal memory was assessed by a 15-word list learning task with three learning trials and free written recall at the end of each trial, therefore the maximum score achievable was 45. The ACE-III scale is the most comprehensive test of cognitive state, developed for use in clinical settings. It includes five subdomains that assess attention, memory, fluency, language and visuospatial ability, and has a maximum score of 100, with a quasi-normal distribution. Recent studies demonstrate the validity of ACE-III for diagnosing mild cognitive impairment, Alzheimer’s disease and dementia [2) was calculated from heights and weight measured by nurses at age 69; heights were measured to the nearest millimetre using a Leicester stadiometer  and weights to the nearest 100 g using Tanita weighing scales .Childhood cognition, own socioeconomic position (SEP), and contemporaneous BMI and depression were identified as potential confounders. Childhood cognitive ability was tested at age 15 using the Heim AH4 test of verbal and non-verbal ability  Watts-VeDepression was assessed at age 69 using responses to questions in the depression subscale of the General Health Questionnaire-28, a screening tool used to detect risk of psychiatric disorders . Responsn = 72 participants) using 20 multiply imputed datasets which were combined with Rubin’s combination rules [We initially examined how vertical impacts related to cognitive function by plotting mean scores for each cognitive test across quartiles of low, medium and high impacts, and tested trends using an extension of the Wilcoxon rank-sum test (Cuzick’s test for trend). Separate linear regression models were then used to examine associations between each PA impact measure  and each cognitive score. Accelerometer data were log-transformed due to their skewed distributions, and model estimates presented as SD difference in each cognitive score per doubling in the number of impacts. Interaction terms were used to test sex differences, and subsequently men and women were combined, with adjustment made for sex after little evidence of interaction was found. Three models were fitted to test associations between PA within each impact band and each cognitive score; a sex-adjusted model which was subsequently further adjusted for SEP, BMI and depression, and then additionally for childhood cognition. Models were fitted after multiple imputation of missing confounders (n = 57), walking restricted due to pain (n = 114), regular mobility aid use (n = 29), falls in the past year (n = 136) and fractures since age 45 (n = 231). This information was captured by a self-reported questionnaire left with participants to complete and return with their accelerometer. Finally, we compared multiple imputation results to complete-case analyses.We investigated if any associations found for specific impact levels were independent of total PA by fitting additional models with mutual adjustment for PA within other impact bands. We also examined if musculoskeletal or functional problems influenced findings by repeating the main analyses after excluding in turn those with difficulties walking i.e. noticeable limp (2) and depression scores (0.67 vs. 0.84) and slightly better adult cognitive scores . Higher proportions of those with valid accelerometer data were in the most advantaged occupational classes (53.5% vs. 45.1%). Vertical impacts from PA comprised 94.3% low magnitude impacts (0.5 < g < 1.0), 5.2% medium impacts (1.0 < g < 1.5 g), and only 0.5% higher impacts (> 1.5 g); men accumulated higher counts of low, medium and higher impacts than women  had data on adult cognitive scores. (Table P trend =0.01), 15.1 for medium impacts (P trend = 0.2) and 14.5 for higher impacts (P trend = 0.2). The equivalent differences in mean ACE-III scores were 1.9 for low impacts (P trend = 0.02) and 1.2 for both medium and high impacts (P trend = 0.3). Similar but less pronounced trends were observed for word learning test scores; equivalent differences were 0.61 for low impacts (P trend = 0.1), 0.55 for medium impacts (P trend = 0.5) and 1.3 for high impacts (P trend = 0.5).There were trends of better performance in the letter search task and the ACE-III across higher quarters of impacts; however, differences were greater for low impacts than medium or higher impacts Fig. . DiffereFigure Greater counts of high impacts (> 1.5 g) were associated with modestly higher scores on the word learning test , letter search task  and the ACE-III scale  in sex-adjusted analyses .The estimates of association between low impacts and cognitive scores strengthened but confidence intervals were wider after mutual adjustment for medium and higher impact PA: letter search task = 0.18 (0.05 to 0.31), word learning test = 0.04 (− 0.06 to 0.13), ACE-III = 0.08 (− 0.01 to 0.17). The weak association between vertical impacts > 1.5 n = 529), no noticeable limp = 0.10 , walking unrestricted by pain = 0.11 , no falls in the past year = 0.06 , no fracture since age 45 = 0.12 , The equivalent differences in letter search task score for high impacts were:, no mobility aid use = 0.05 , no noticeable limp = 0.03 , walking unrestricted by pain = 0.05 , no falls in the past year = 0.04 , no fracture since age 45 = 0.03 . Finally, findings were broadly similar for participants with non-missing data on confounders (n = 486); though the association between higher impacts (> 1.5 g) and word learning test score was stronger in the reduced sample  SD difference in letter search task per doubling in number of low impacts were: no mobility aid use = 0.13 . These associations were independent of measured confounders including childhood cognition and were robust to exclusion of those with musculoskeletal and functional problems and to adjustment for higher impact PA. We also found evidence of positive but weak associations between impacts > 1.5 This is the first study to objectively quantify physical activity according to level of vertical impacts from ground reaction forces and examine how both low and higher impact activity relates to cognitive performance in later life. Our finding that low impact PA was positively related to cognition is consistent with findings from a large study of Chinese older adults showing that regular low impact mind-body exercises like Tai Chi and yoga were associated with lower risk of dementia . The weaNearly all PA in this study was low impact. We suspect that much of the PA producing low impacts in this population to be from lower intensity activities, predominantly walking. In that case, our results would be consistent with findings in older women showing that reported walking was associated with better cognitive performance  and thatSome of the mechanisms underlying the associations found between low impact PA and cognition may operate through direct influences of total PA on brain function as well as by preventing diseases that impair cognition . These mA major strength of this study is the novel use of raw accelerometer data to parameterise PA according to vertical impact and provide new insights into associations with cognitive function in later life , 29. UseIn conclusion, we used raw accelerometer data to describe PA according to level of vertical impact and investigated its association with cognitive function in a 69-year old British birth cohort. We found that PA producing low magnitude impacts, which made up the majority of all PA in this older population, was associated with faster visual processing speed independently of childhood cognitive ability and other confounders. Further studies are required to determine the causal nature of this association.Additional file 1:n = 486). Model 1: adjusted for sex. Model 2: adjusted for sex, SEP, BMI and depression. Model 3: as for model 2 plus adjustment for childhood cognition. Horizontal bars reflect 95% confidence intervals (CI). (TIF 1536 kb)Standard deviation difference in cognitive test scores per doubling in number of low (0.5 ≤ g < 1.0), medium (1.0 ≤ g < 1.5) and higher (≥ 1.5 g) magnitude impacts in the reduced sample i.e. non-missing data on confounders (