Behaviour models are the most commonly used input for predicting the reliability of a software system at the early design stage. A component behaviour model reveals the structure and behaviour of the component during the execution of system-level functionalities. There are various challenges related to component reliability prediction at the early design stage based on behaviour models. For example, most of the current reliability techniques do not provide fine-grained sequential behaviour models of individual components and fail to consider the loop entry and exit points in the reliability computation. Moreover, some of the current techniques do not tackle the problem of operational data unavailability and the lack of analysis results that can be valuable for software architects at the early design stage. This paper proposes a reliability prediction technique that, pragmatically, synthesizes system behaviour in the form of a state machine, given a set of scenarios and corresponding constraints as input. The state machine is utilized as a base for generating the component-relevant operational data. The state machine is also used as a source for identifying the nodes and edges of a component probabilistic dependency graph (CPDG). Based on the CPDG, a stack-based algorithm is used to compute the reliability. The proposed technique is evaluated by a comparison with existing techniques and the application of sensitivity analysis to a robotic wheelchair system as a case study. The results indicate that the proposed technique is more relevant at the early design stage compared to existing works, and can provide a more realistic and meaningful prediction. Observation of the trends in a range of fields indicates a variety of computer software applications. Computer software can be found embedded in many devices and equipment, such as hand phones, automobiles and aircraft. In addition, software is increasingly used to support critical business applications and industrial processes. Most of these fields depend on software for their basic functioning. Software failure can lead to critical events and fatal consequences in safety-critical applications as well as in business applications. In order to meet customer expectations and needs, the software must have high reliability. The increasing demands of software functionalities are leading to various issues including the scalability and degree of concurrency of the software system. Customer satisfaction is also a serious challenge; thus, software reliability engineering must live up to the needs of today’s complex software systems and their specific challenges .The reliability approach is formalized to explain the failure behaviour within a system. Software reliability is defined as the probability that the software system will perform a required function correctly (failure-free) in a stated environment for a specified period of time. Due to the heterogeneity of the execution environment and the development methodology of current software systems, a failure broadly can mean that the software system is unable to deliver the expected service and is not capable of resuming its service to the state prior to being interrupted. Several kinds of failures are possible during service execution, such as faults in the implementation of the software components, hardware failure and network failure. Hardware failure is due to an unreliable hardware resource, and network failure occurs because the message is lost or there is a problem in inter-component communication ,3. PrediBased on the lifecycle of the reliability measurement, the reliability measures taken early while building and later during the testing or post-deployment ,5,6. TheA software development team is a cohesive coalition of individuals working together towards a common goal . The strBased on behaviour models, several techniques can be used to evaluate the reliability of software at an early stage and identify the reliability-critical elements of the architecture. However, the existing techniques suffer from a number of drawbacks that limit their applicability and accuracy.First, according to ,10 severSecond, most of the existing techniques ,10,11,12The paper is structured as follows. We first highlight the research gap in early reliability prediction and then discuss the related works in Section 2. Section 3 defines the proposed technique’s elements and construction steps and illustrates the applicability of the proposed technique using an illustrative example. In Section 4, we evaluate and illustrate the applicability of the proposed technique using a real world case study. The last section concludes the paper and provides an outline of future works.During the last decade, many techniques have been proposed to predict software reliability in the early design stage depending on behavioural models; these techniques address different problems and challenges. However, individual component reliability is an integral issue that should be considered in predicting the reliability of a software system at the early design stage ,14. ExceThe work by ,10,11,15On the other hand, the work by  proposesThe reliability of a component is predicted based on the component’s architectural design and the operational data relevant to this design. The component architectural design is modeled or constructed in the form of a state machine. This state machine can be derived from the code using induction algorithms or from the requirements specification using behaviour synthesis algorithms. This paper’s work is intended for the early design stage before the coding stage; therefore, the proposed technique is built through the behaviour synthesis. Synthesizing a behaviour model or deriving a state machine from requirements specification is the starting point for the proposed technique.For ease of exposition, the proposed technique is depicted as a three-phase process as shown in A dependency graph is selected to represent the component structure and behaviour for two reasons. First, it facilitates the capture and modeling of an individual component’s behaviour (including the loop entry and exit points) and includes the consideration of that information in the reliability computation. This aspect is overlooked in most current component reliability techniques. Second, it is typical to use a specific computation algorithm, namely, the tree transversal algorithm, to allow for a tractable solution.The process of synthesizing the component behaviour from scenario specifications as a popular requirements elicitation tool involves three activities: preparing scenarios, translating the component instances in each scenario to FSMs, and merging the FSMs of each component into one state machine model such as the labelled transition system (LTS). In order to define how the behaviour models can be synthesized, this section briefly reviews our previous research work , which iBriefly, the system scenarios in this paper’s work were written using a scenario language called the scalable triggered scenario (s-TSs) language. Triggered scenario languages provide syntactic constructs for describing the conditional or causal relations between sequences of actions. Scenarios in a language like live sequence charts, are described in conditional form  and existential. In triggered language, scenarios are described in universal form with existential semantics. This type of modeling provides a good fit with use cases which is the primary form of requirements elicitation. An example of an existential scenario is the automatic teller machine (ATM) scenario which describes a statement like “If the user inserts a valid card into the ATM, and then enters the correct password, she/he shall be able to request cash and have it dispensed by the ATM”. This statement is also conditional in the sense that requesting and obtaining cash is expected to be possible if the user has inserted a valid card and input the correct password. An example of a universal statement is: “If the user inserts a valid card into the ATM, and then enters an invalid password, then she/he must receive the password incorrect message”. The s-TSs facilitates the writing of statements like “If the user inserts a valid card into the ATM, and then enters a valid password, then she/he must able to see the ATM options, otherwise she/he must receive the password incorrect message”. The last statement in a universal form, but more concise and compact . s-TSs use constructs such as implied triggers and branching messages to compact the statements. The s-TSs enhance the current triggered scenario languages ,28 by ad.Once the scenarios are prepared (annotated and propagated), we are ready to synthesize a behaviour model for each component in the system. The strategy starts by generating a number of FSMs for the component (one FSM from each scenario). Thus, each FSM represents the behaviour of the component corresponding to a specific scenario from the set of system scenarios. These FSMs will later be merged (in Phase3) to produce a complete behaviour model of the component. In order to convert each component instance within a scenario to FSM, pre-post conditions values and operations (incoming and outgoing messages) of this component instance will be translated to states and transitions, respectively. Fig 2In the final activity in behaviour model construction, we merge the different FSMs of the component by identifying identical terminal and starting states. Two different FSMs will be merged if and only if the terminal state of one is similar to the starting state of the other. The merging transition will be created from a terminal to a start . The similarity between the states is determined based on the state vector values of the states. The final output of this phase is the LTS which represents the behaviour of the component. A CPDG is a directed graph that reveals the component’s structure and behaviour, which determine the component’s reliability. The use of a probabilistic graph is a classical method in software engineering applications. Baah et al.  propose Preparing the CPDG involves two activities: constructing the CPDG, and generating the operational data. In the construction activity, all the elements of the CPDG are defined based on the basic notation and definitions of the CPDG and the synthesized behaviour model of the targeted component. The synthesis of the behaviour model was already described in relation to the previous phase. The next subsection defines the notations and parameters of the CPDG. Then, the operational data generation activity which provides the data used to assign values to all the CPDG parameters is described.Briefly, the CPDG construction requires the identification of its basic notation and definitions. In graph theory, a directed graph G is defined as a set of pairs, G = , where:N represents a set of nodesE represents a set of edgesFor CPDG the formal definition is:G =  where:N is a finite set of nodes representing the component’s statesS, Entry, Exit} where:N = {Si, RSi> where:S is defined by the tuple <Si is a unique identification of the component’s statesRSi is the reliability of a state i (it is a probability that indicates that the component will pass the current state correctly (fault free)Entry is a virtual state pointing to the first state of the component’s execution (it has no input transition and it reliability is 1)Exit is a virtual state pointing to the termination of the component’s execution (it has no outgoing transition and it reliability is 1)E is a finite set of edges representing the transitions between the component’s statesE = {T}.PTij or PTiExit where:T is defined by PTij is the probability of transition from state i to state j, which is the probability that the next state will be executed after the current state PTiExit is the probability of transition from state i to exit state.1,S2,S3,…,Sn}, a transition matrix A = {aij}that represents the transition probabilities from state Si to state Sj, observations O = {O1, O2, O3, …, Om}, and an observation probability matrix E = {eik} that represents the probability of observing event Ok in state Si. In this paper’s work, the component behaviour model that was synthesized in the previous phase will be mapped to define the HMM states S and transition matrix A = {aij}. The observations O and the observation probability matrix E = {eik} are identified based on the data gathered from similar function components, domain knowledge, and analysis of the component architectural model using the technique proposed by [The operational data describe the behaviour of the component quantitatively. The data identify an ordered set of operations that the software component performs along with their associated probabilities. At the early stages of software development, the operational data on a given component may not be available, particularly in the case of newly designed components, and a design time reliability prediction technique must take this uncertainty into consideration. To generate operational data in this paper’s work, the concept of the representative operational profile that has been used in the literature ,12, relyposed by .ij}and E = {eik},gives the best values for the transition and observation probability matrices A and E. In brief, the data obtained from the Baum–Welch algorithm represent the operational data of the component based on the training data, which represent the component’s behaviour based on its architectural design. However, all these details are relevant to operational profile modeling, which is beyond this paper’s scope. The operational data are utilized directly to predict all the CPDG parameters; for instance, if the state Si fails 5 times each 100 execution, it means the reliability of state i is (RSi = 0.95). Similarly, the operational data give the frequencies of the transitions among the states which translate the transition probabilities PTij into the CPDG.Baum–Welch is an iterative optimization technique used with HMM to approximate the best transition and observation probabilities. It is defined as an expectation–maximization algorithm that, given the number of states S, number of observations O, and a set of training data A = {aAfter constructing the CPDG and defining its related parameters, an algorithm to estimate the component reliability (CR_Estimate) is developed. The algorithm estimates or computes the component reliability based on the CPDG branches and their relevant parameters. In the CPDG, each path represents consecutive states and transitions. The algorithm traverses the CPDG thereby computing the paths’ reliabilities. The computation is based on By adopting the formula in  the pathk where k = 1, 2, …, K.K is the total number of paths.n is the number of states in the path.i) is the probability of visiting each state i belonging to the path from the initial state. From the CPDG definitions, the probability of transition to the first state is 1; then Pr(vi) can be rewritten as:Pr.Using the value of the Rtemp, the component reliability is then computed using Algorithm 1 Component reliability estimation algorithm: CR_EstimatefunctioncomputRc1. Initialization: pthTemp = 1,transTemp = 1, it_no = 0; Rtemp = 0;2. s = Stack.Create;3. SI, RSI, it_no, transTemp, pthTemp);4. s.push ;6.   ifSi = = Exit {Exit node}7.    8.     Rtemp+ = PthTemp;9.     k++, it_no = 0;else10.    for it_no = 0 to max_it do11     for allSj, RSj ∈ Si successors do12.      PTi,j;13.       transTemp* = RSj,transTemp);14.       pthTemp* = power;15.       s.push. Based on the result shown in Subsumption component of the wheelchair and some of operations’ execution of the avoid-component are complemented by an operation that belongs to the Subsumption. Thus, it is difficult to determine whether a specific failure was caused by the avoid-component or other operation in the Subsumption. In fact, as discussed in the introduction of this paper, the absence of the run time information which is used in the component reliability measurement is the main reason that leads to develop the CR_Estimate Algorithm and the related early prediction algorithms.In order to investigate the computational accuracy of the CR_Estimate Algorithm, we need to compare the computed reliability values with measured values of the component. In the early prediction known as the measured reliability value will not be available, due to the absence of runtime information. Furthermore, obtaining a measured value of individual component reliability is not an easy task. To obtain the reliability of individual component, we need to define all the failure modes caused by the targeted component. Note that the component usually used as part of other components, therefore it is difficult to determine which component is causing a specific failure independently. For instance, the avoid-component is part of a help of other related works such as the work presented in the study [Therefore, in the investigation of computational accuracy of the algorithm we will try to measure the difference between the expected and computed reliability value of the component. The expected value can be elicited from information related to analogous components with similar operations and information obtained from a domain expert, such as the information shown in he study .N operations in the component, and Fi is the expected failure probability of the ith operation, the expected reliability of the component Ex (Rc) can be elicited by the following equation:If we have c) = 0.973. Therefore, the difference between the computed value and the expected is 0.00734. By applying the same way for the algorithm presented in [c) = 0.910, while the computed was 0.9223, so the difference is 0.0123. Based on this simple comparison, our computed value seems more close to the expectation. The purpose of this investigation is just to check whether the accuracy of the computed value is logically acceptable or not. While the main comparison between this research and the related works including the work in [Based on Sensitivity analyses, which vary certain parameters of the behaviour model in order to perceive the effects on the prediction results, are an important and common way to gain more insights into the reliability characteristics of the component under study ,16,39. Ustate1 which is related to the receipt of the signal from the IR sensor. As the reliability of this state decreased, the component reliability dramatically decreased. This is due to the fact that this state is at the heart of the avoid-component and therefore any faults in this state will easily propagate and affect the correct operation of the component. In addition, from our CPDG shown in state1 will visit twice per each execution cycle. Furthermore, state1 belongs to all CPDG paths. On the other hand, the reliability of the component doesn’t vary significantly with the variation in the reliability of state3 and state5. This is due to the weak probability of visiting these; for example, the transition probability of state3 only equals 0.0971. On the contrary, the component reliability is more sensitive to the reliability of state2 and state4; this is due to their higher transition probability as compared to state3. Among the other states, state6 and state7 are similar to state1. Both state6 and state7 belong to more than one path in CPDG; thus, the component reliability is more sensitive to these states than in the case of all other states except state1.The analysis results demonstrate and identify the criticality of each state and the operation that led to it within the avoid-component clearly.From Activation finished, Set avoid active with Direction change finished had a similar impact on component reliability, as did Activate obstacle Right with Activate obstacle Left. Component reliability was particularly sensitive to the signal from IR sensor, which plays the central role in avoiding an obstacle. The higher impact of this operation is due to the multiple invocations per each path traversal. Hence, it is most beneficial to focus on improving the reliability of the signal from IR sensor operation.In conclusion, the derivation and identification of the component states, together with the operations that lead to them, in relation to reliability prediction for the avoid-component of the wheelchair system are indeed essential for identifying the critical states and operations in the component. This type of analysis result could provide valuable information that will enable a component’s architect to know the effectiveness of the states and the operations quantitatively. Moreover, sensitivity analyses on the wheelchair demonstrate that the proposed reliability technique is meaningful and useful from the perspective of making design decisions, as the reliability values obtained are able to aid the architect in evaluating design alternatives.This section investigates the improvement of the proposed technique as compared with the existing works. The investigation was based on a comparison with the related works as discussed above in Section 2. To fairly compare, we chose the three most similar techniques with the proposed technique, as shown in The comparison results in From the comparison result in In this paper, a technique for the early reliability prediction of software components is presented. The proposed technique is shown to have the potential to address the various challenges related to reliability prediction at the early design stage, such as capturing and modeling component behaviour based on the requirements specification. In the proposed technique, a state machine that represents a component’s behaviour is synthesized to reveal the component’s dynamic behaviour by describing all the possible interaction sequences of the component. The state machine is utilized as a base to generate the component-relevant operational data with the support of data gathered from similar function components, domain knowledge, the HMM, and the Baum–Welch algorithm. Moreover, the state machine is mainly used as a source for identifying the nodes and edges of a probabilistic dependency graph, called the CPDG. The generated operational data are used to identify the values of the CPDG parameters. Component reliability is computed through a tree transversal algorithm called the CR_Estimate which utilizes the CPDG as input.The requirements specification of an ATM system was used to illustrate the applicability of the proposed technique. A case study for the control system of a robotic wheelchair system was used to evaluate the proposed technique. The evaluation results of applying CR_Estimate in the case study indicate that the proposed technique provides meaningful reliability prediction in the context of the early stages of software development. The results clearly identified the relationship between the execution cycles and the component reliability. In addition, the results identified the critical states of the component that would require intensive testing and validation. The comparison of our technique and the existing works showed that our proposed technique provides a realistic and meaningful evaluation of a component’s reliability, which leads to accurate prediction.There are several open issues for future work. It is noted that the reliability prediction of software components may be applied to components and their behaviour in isolation, such as an off-the-shelf component, which is not part of any system. However, the prediction may be more meaningful when the component is considered in the context of a system. Therefore, we intend in future research to construct a system-level reliability approach that can utilize the results obtained through the proposed technique. Another plan is to enhance the accuracy of the operational profile that predicts the transition probabilities among the components’ states through incorporating other machine learning techniques such as the hierarchal hidden Markov model. Further


Background: Hypertrophic cardiomyopathy (HCM) patients often present with diastolic dysfunction and a normal to supranormal systolic function. To counteract this hypercontractility, guideline therapies advocate treatment with beta-adrenoceptor and Ca2+ channel blockers. One well established pathomechanism for the hypercontractile phenotype frequently observed in HCM patients and several HCM mouse models is an increased myofilament Ca2+ sensitivity. Nebivolol, a commonly used beta-adrenoceptor antagonist, has been reported to lower maximal force development and myofilament Ca2+ sensitivity in rabbit and human heart tissues. The aim of this study was to evaluate the effect of nebivolol in cardiac muscle strips of an established HCM Mybpc3 mouse model. Furthermore, we investigated actions of nebivolol and epigallocatechin-gallate, which has been shown to desensitize myofilaments for Ca2+ in mouse and human HCM models, in cardiac strips of HCM patients with a mutation in the most frequently mutated HCM gene MYBPC3.Methods and Results: Nebivolol effects were tested on contractile parameters and force-Ca2+ relationship of skinned ventricular muscle strips isolated from Mybpc3-targeted knock-in (KI), wild-type (WT) mice and cardiac strips of three HCM patients with MYBPC3 mutations. At baseline, KI strips showed no difference in maximal force development compared to WT mouse heart strips. Neither 1 nor 10 μM nebivolol had an effect on maximal force development in both genotypes. 10 μM nebivolol induced myofilament Ca2+ desensitization in WT strips and to a greater extent in KI strips. Neither 1 nor 10 μM nebivolol had an effect on Ca2+ sensitivity in cardiac muscle strips of three HCM patients with MYBPC3 mutations, whereas epigallocatechin-gallate induced a right shift in the force-Ca2+ curve.Conclusion: Nebivolol induced a myofilament Ca2+ desensitization in both WT and KI strips, which was more pronounced in KI muscle strips. In human cardiac muscle strips of three HCM patients nebivolol had no effect on myofilament Ca2+ sensitivity. MYBPC3 (encoding cardiac myosin-binding protein C) and MYH7 (encoding β-myosin-heavy chain)  filling time and reducing outflow tract obstruction  is the most frequent cardiac genetic disease primarily caused by mutations in sarcomeric protein genes  who underwent septal myectomy due to outflow tract obstruction. The material was taken with written informed consent of the donor and with written approval of the local ethical boards. The study has been carried out in accordance with The Code of Ethics of the World Medical Association (Declaration of Helsinki).Human myocardial samples were obtained from three HCM patients carrying heterozygous Mybpc3 KI cardiomyopathy mouse model was generated by the targeted insertion of a G>A transition on the last nucleotide of exon 6  and comply with the ARRIVE guidelines . All experimental procedures were in accordance with the German Law for the Protection of Animals and the protocol was approved by the Ministry of Science and Public Health of the City State of Hamburg, Germany (Org 653).The 2+ relationships, trabeculae were prepared from ventricular endocardial surface of WT and KI mice or human myocardium of a septal myectomy , calculated by 2πr2 assuming a circular shape, nWT = 17, nKI = 18, nhuman = 57. Strips were permeabilized in relaxing solution (pCa 9) in EGTA-buffer   by mounting them between a force transducer and a length controller. Strips were stretched above slack length until they developed force in activating solution (pCa 4.5) at 15°C. For contraction-relaxation cycles strips were kept in pCa 9 to achieve full relaxation. Then they were moved to pCa 4.5 until maximal force development was reached. Maximal force was related to cross-sectional area (mN/mm2). For force-Ca2+-curves they were exposed to increasing Ca2+ concentrations from pCa 9 to pCa 4.5 in EGTA-buffer. Force development was measured in each pCa solution. Measurements were repeated in the presence of 1 or 10 μM nebivolol  or 30 μM epigallocatechin-gallate (Sigma Life Sciences) after 5 min preincubation in relaxing solution . A value of P < 0.05 was considered statistically significant.Data were expressed as mean ± SEM. Comparisons were performed by paired or unpaired Student's 2+ sensitivity. Since nebivolol has been reported to lower maximal force development and to desensitize rabbit and human cardiac myofilaments  shifted the force-Ca2+ relationship to the right resulting in a lower pCa50, whereas in KI strips both 1 and 10 μM lowered pCa50  to the right  At baseline, permeabilized left ventricular trabeculae isolated from Mybpc3 KI mouse hearts showed no difference in maximal force development compared to WT mouse heart strips. (2) Neither 1 nor 10 μM nebivolol had an effect on maximal force development in both genotypes. (3) 10 μM nebivolol induced myofilament Ca2+ desensitization in both WT and KI strips and this effect was more pronounced in KI muscle strips, respectively. (4) Nebivolol had no effect on Ca2+ sensitivity in cardiac muscle strips of three HCM patients with MYBPC3 mutations, whereas 30 μM of EGCg induced a right shift in the force-Ca2+ curve.HCM patients often present with a normal to supranormal systolic function and diastolic dysfunction. To counteract this hypercontractility, guideline therapies advocate treatment with beta-AR and Ca2+ sensitivity in mouse strips. The mechanism behind this is unknown so far. In analogy to the mouse results, 1 and 10 μM nebivolol had no effect on maximal force development in human tissues. In contrast to the observations made in mouse strips, it did not impact on myofilament Ca2+ sensitivity.In mice, nebivolol did not influence maximal force development. On the other hand, it affected myofilament Ca2+ desensitizing effect in KI strips at both 1 and 10 μM, whereas in WT strips only 10 μM had an effect and no effect at all in human HCM tissues remains unclear. As mentioned before, discrepancies concerning the effects of nebivolol on maximal force development and myofilament Ca2+ sensitivity in cardiac muscle strips have been previously described. Whereas Zeitz et al. reported that 1 μM nebivolol lowered maximal force development and myofilament Ca2+ sensitivity in skinned rabbit and human trabeculae  investigating the effects of nebivolol and carvedilol on diastolic function of the left ventricle in older HF patients with preserved EF  Our study does not explain the precise mechanism of Ca2+-desensitization of nebivolol in mouse heart tissue. (3) The Ca2+ desensitizing effect of nebivolol in mouse tissues occurred at concentrations which were above the plasma concentrations (0.8–3.7 nM) observed in humans  The 2+ desensitization in both WT and KI mouse cardiac muscle strips, which was more pronounced in KI muscle strips. In human cardiac muscle strips, nebivolol had no effect on force development and myofilament Ca2+ sensitivity. Further studies should investigate the exact target and mechanism for Ca2+ desensitization in mouse cardiac tissues in order to be able to develop modified compounds with even more potency and specificity for use in human tissue.Nebivolol had no effect on maximal force, but induced a myofilament CaSS and NK: Isolation and treatment of cardiac muscle strips and execution of experiments. LC: Analysis and interpretation of data, and correction of the manuscript. FF: Conception and design of research, execution of experiments, analysis and interpretation of data, figure preparation, and drafting of the manuscript. All authors critically discussed the results, and reviewed and approved the manuscript before submission.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Activation of βARs allows rapid enhancement of myocardial function in order to fuel the muscles for running and fighting in a fight‐or‐flight response. Likewise, βARs become activated during cardiovascular disease in an attempt to counteract the restrictions of cardiac output. However, long‐term stimulation of βARs increases the likelihood of cardiac arrhythmias, adverse ventricular remodelling, decline of cardiac performance and premature death, thereby limiting the use of βAR agonists in the treatment of heart failure. Recently the endogenous Raf kinase inhibitor protein (RKIP) was found to activate βAR signalling of the heart without adverse effects. This review will summarize the current knowledge on RKIP‐driven compared to receptor‐mediated signalling in cardiomyocytes. Emphasis is given to the differential effects of RKIP on β AAVadeno‐associated virusAC6adenylyl cyclase 6βARβ‐adrenergic receptorβARKctβ‐adrenergic receptor kinase, C‐terminusCaMKII2+/calmodulin‐dependent protein kinase IICacAMPcyclic adenosine monophosphatecMyBPCcardiac myosin binding protein CEpacexchange protein directly activated by cAMPERK1/2extracellular signal‐regulated protein kinases 1 and 2GPCRG‐protein‐coupled receptorGRKG‐protein‐coupled receptor kinaseiGinhibitory G‐proteinsGstimulatory G‐proteinKOknock‐outLTCC2+ channelL‐type CaMEKmitogen‐activated protein kinase kinaseNCXsodium–calcium exchangerPDEIIIphosphodiesterase IIIPEBPphosphatidylethanolamine‐binding proteinPKAprotein kinase APKCprotein kinase CPLNphospholambanPMCA2+‐ATPasesarcolemmal CaRKIPRaf kinase inhibitor proteinRyR2ryanodine receptor 2S100A1S100 calcium binding protein A1SERCA2a2+‐ATPasesarco‐/endoplasmic reticulum CaSRsarcoplasmic reticulumTnItroponin Iet al. Heart failure occurs if cardiac output is reduced to an extent that it cannot meet the body's needs. It represents one of the leading causes of morbidity and mortality in developed countries and results from the loss and/or dysfunction of cardiomyocytes due to literally any insult to the heart, most frequently chronic arterial hypertension, myocardial infarction, aortic stenosis or infectious diseases. The activation of the sympathetic nervous system via β‐adrenergic receptors (βARs) is the most important compensatory mechanism in heart failure, acting to stabilize the hemodynamic situation by accelerating cardiac contraction and relaxation (Ponikowski 2+) are the critical intermediary that translates sympathetic activity into myofilament movement. Changes of beat‐to‐beat myocyte Ca2+ cycling are also among the hallmarks of heart failure. Further, local Ca2+ release events (Ca2+ sparks) and/or altered Ca2+ sensitivity of cardiomyocytes contribute to contractile dysfunction and increase the risk of cardiac arrhythmias in failing hearts as well as in diseases like inherited cardiomyopathy or early after myocardial infarction , speed of relaxation (positive lusitropy), atrioventricular conduction (positive dromotropy) and heart rate (positive chronotropy)  that stimulate adenylyl cyclases to produce the second messenger cyclic adenosine monophosphate (cAMP), which in turn activates the cAMP‐dependent protein kinase A (PKA). In cardiomyocytes, regulators of beat‐to‐beat Ca2+ cycling and sarcomere proteins represent major substrates of PKA. Activation of PKA causes phosphorylation of L‐type Ca2+ channels (LTCCs). This increases Ca2+ influx; phosphorylation of phospholamban (PLN), which accelerates the reuptake of Ca2+ into the sarcoplasmatic reticulum (SR); phosphorylation of ryanodine receptors 2 (RyR2), which increases SR Ca2+ release; phosphorylation of troponin I (TnI) and of cardiac myosin binding protein C (cMyBPC), which decreases myofilament Ca2+ sensitivity; and phosphorylation of titin, which reduces the sarcomeric passive stiffness , a kinase that also impacts on Ca2+ homeostasis by phosphorylation of RyR2, PLN or cMyBPC, thereby further potentiating βAR‐mediated cardiac contraction and relaxation . In line with this, the unfavourable outcome of the Ile164 polymorphism was suggested to result from the loss of β2ARs coupled to Gi and their protective effects on apoptosis  improve patients’ symptoms and significantly promote survival when applied carefully at slowly increasing dosages. Multiple studies within the last two decades have shown that β‐blockers improve survival for chronic heart failure by up to 30% , an enzyme that degrades cAMP; activation of PKA; inhibition of protein phosphatase 1, an enzyme that reduces PKA‐mediated activation of calcium cycling proteins; or activation of CaMKII , which plays an important role in diastolic Ca2+ removal. SERCA2a activity was modulated via deletion of the SERCA2a inhibitor PLN, overexpression of SERCA2a or overexpression of S100 calcium binding protein A1 (S100A1). Further, the LTCC was targeted using the Gβγ scavenger C‐terminus of the β‐adrenergic receptor kinase (βARKct), which leads to disinhibition of G‐protein (Gβγ)‐mediated inhibition of the channel  safely increased left ventricular function beyond standard heart failure therapy in a recently published phase 1/2 trial of AC6 gene transfer in heart failure patients  family, which has been characterized as a modulator of signal transduction cascades in mammalian cells and has been reviewed in detail by Trakul & Rosner , Granovset al. . PEBP/RK. et al. . This caet al. et al. et al. et al. et al. et al. et al. Even though other kinase signalling cascades such as the nuclear factor κ‐light‐chain‐enhancer of activated B‐cells (NFκB) and glycogen synthase kinase‐3β are also known to be regulated by RKIP in cultured cells, thus far only Raf‐1, MEK1 and ERK2 as well as GRK2 have been identified as direct interaction partners of RKIP of which only Raf‐1 and GRK2 have been validated under endogenous conditions 1AR–Gs signalling, which results in enhanced contraction and relaxation via increased PLN and TnI phosphorylation and subsequently increased SERCA2a activity, higher SR Ca2+ load and decreased Ca2+ sensitivity of myofilaments. Cardiac contractility of RKIP‐overexpressing mice was improved compared to control animals up to an age of at least 12–14 months; and lifespan of RKIP‐overexpressing mice under these conditions was at least as long as of non‐transgenic mice 1AR–Gs signalling, RKIP‐stimulated hearts are still able to respond adequately to physiological stress situations because the size of the dobutamine response of RKIP‐overexpressing and wild‐type hearts is similar. This moderate or submaximal activation may play an important role for the observed reduction of cardiomyocyte apoptosis, interstitial fibrosis, brain natriuretic peptide and collagen expression in RKIP‐overexpressing mice compared to wild‐type controls and the overall well‐tolerated positive inotropic phenotype of RKIP‐overexpressing mice 1AR–Gs‐signalling that stimulates the activity of both PKA and CaMKII, RKIP activates β2AR–Gi in mouse hearts. The simultaneous activation of β2AR–Gi within the transverse (t)‐tubular region prevents the adverse effects of mere β1AR–Gs, such as diastolic Ca2+ leak and cardiac arrhythmia due to hyperphosphorylation and subsequent activation of the RyR2 or hyperphosphorylation of the LTCC. These RKIP effects appear to be mediated by β2AR–Gi signalling since this protection is absent in RKIP‐overexpressing mice lacking β2ARs and in the presence of the Gi inhibitor pertussis toxin et al. et al. RKIP was found to inhibit βAR downregulation and thereby secures sustained positive inotropy, which is not achieved by direct agonist‐mediated βAR stimulation (Lorenz (5)−/−) dramatically increased it. This effect is β2AR dependent since the protection from apoptosis is absent in RKIP‐transgenic mice lacking the β2AR. Interestingly, β2AR–Gi is known to stimulate the kinase Akt, which in turn mediates anti‐apoptotic effects  while RKIP deficiency exaggerated heart failure under these conditions. AAV9‐mediated gene transfer protected wild‐type and RKIP knockout mice from transverse aortic constriction‐induced heart failure (Schmid Ser153), but in the absence of Ser153 phosphorylation it acts as a Raf‐1 inhibitor. In the heart, Raf–MEK–ERK1/2 signalling promotes cell survival  but rather circumvent activation of the RyR2  or even protect from RyR2 sensitization   that counteracts several maladaptive β1AR effects such as RyR2 sensitization, diastolic Ca2+ leaks and arrhythmia as well as apoptosis and fibrosis. Indeed, ‘sole’ β1AR activation as provided in RKIP transgenic mice lacking the β2AR (β2KO) increased cardiac contractility, but also reduced overall survival of ageing RKIP transgenic mice (RKIP/β2KO) compared to β2KO controls , 1% by the sarcolemmal Ca2+‐ATPase (PMCA) and 1% by the mitochondrial Ca2+ uniporter) , the SERCA2a regulator PLN plays a pivotal role in modulating myocyte Ca2+ distribution and kinetics. PLN inhibits SERCA2a, thereby attenuating the rate of Ca2+ transport to the SR. Phosphorylation of PLN by PKA at serine 16 can almost fully relieve this inhibitory effect leading to a pronounced acceleration of SR Ca2+ uptake. As Ca2+ is sequestered by the SR, in the sarcomeres TnI inhibition of actin–myosin interactions is re‐established and myocytes relax  Bers, . Since S2+ cycling. Although the causes of heart failure can vary widely, e.g. myocardial infarction, arterial hypertension, infections or genetic defects, the pattern of abnormal Ca2+ metabolism is relatively uniform , but primarily due to reduced SERCA2a activity. Depression of the Ca2+ pump results from reduced SERCA2a expression in failing hearts, whereas PLN levels remain stable leading to a reduced SERCA/PLN ratio  and threonine 17 (CaMKII site) leading to efficient release of PLN from SERCA2a and subsequent activation of SERCA2a. The RKIP‐induced increase in Ca2+ reuptake during diastole may further be supported by an accelerated Ca2+ release from the myofilaments mediated by enhanced TnI phosphorylation at the serine residues 23 and 24. Further, via GRK inhibition, RKIP prevents βAR desensitization and βAR degradation in a heart under chronic sympathetic stress, which subsequently secures efficient and continuous Ca2+ cycling. In addition, RKIP overexpression is able to prevent a loss of SERCA2a expression in a failing mouse heart, which in turn also ensures effective Ca2+ cycling in cardiomyocytes.RKIP seems to provide a promising approach for the restoration of depressed Ca2+, the enhanced Ca2+ load would explain the hypercontractile phenotype of RKIP‐overexpressing hearts and the improved cardiac function in a mouse model of heart failure due to chronic pressure overload  and both early and delayed afterdepolarizations that trigger aberrant electrical activity and arrhythmias of the heart  accelerates cytosolic Ca2+ elimination by PKA‐dependent phosphorylation of PLN and (3) increases SR Ca2+ filling and therefore the size of the Ca2+ transients. Finally, RKIP overexpression prevented morphological and functional maladaptation of the heart in mice subjected to long‐term pressure overload. Future studies will show if these beneficial effects hold true for the rescue of independent models of heart failure.Pharmacological and gene therapeutic studies are aimed at fixing the Cas signalling/β1AR leading to functional recovery of the heart and (2) the protection of the heart under sympathetic stress from exaggerated β1AR downstream signalling including protection from apoptosis and pro‐arrhythmic adverse effects via β2AR activation. This approach promises a new therapeutic strategy to achieve well‐tolerated long‐term increases in cardiac contractility. RKIP comprises several favourable characteristic effects on calcium cycling, calcium sensitivity, G‐protein recruitment to βARs and a physiological extent or range of βAR activation and has proven protective in murine heart failure. Future studies will further unravel the signalling network induced by RKIP that is responsible for the well‐tolerated mode of βAR activation and evaluate its therapeutic efficacy in various disease entities.RKIP is an endogenous protein that exhibits a combination of favourable effects for heart failure patients: (1) the gain/increase of cardiac contractile efficiency by the activation of GThe authors have no competing interests.All authors have approved the final version of the manuscript and agreed to be accountable for all aspects of the work. All persons designated as authors qualify for authorship, and all those who qualify for authorship are listed.This work was supported by Deutsche Forschungsgemeinschaft  and SFB 1116 (TPA02 to J.P.S.)), by Bundesministerium für Bildung und Forschung ) and by the Ministry for Innovation, Science and Research of the Federal State of North Rhine‐Westphalia (K.L.). A PhD position was awarded to T.B. by the Elite Network of Bavaria within the IDK ‘receptor dynamics’.


Social judgments of faces are thought to be underpinned by two perceptual components: valence and dominance. Recent work using a standard key-press task to assess reward value found that these valence and dominance components were both positively related to the reward value of faces. Although bodies play an important role in human social interaction, the perceptual dimensions that underpin social judgments of bodies and their relationship to the reward value of bodies are not yet known. The current study investigated these issues. We replicated previous studies showing that valence and dominance underpin social judgments of faces and that both components are positively related to the reward value of faces. By contrast, social judgments of bodies were underpinned by a single component that reflected aspects of both perceived valence and perceived dominance and was positively correlated with the reward value of bodies. These results highlight differences in how observers process faces and bodies. Principal Component Analyses (PCA) of a wide range of trait ratings demonstrate that social judgments of faces are underpinned by two perceptual components: valence and dominance ,2. The vBehavioral and neurobiological evidence shows that viewing faces high on traits that are positively correlated with the valence component, such as attractiveness and trustworthiness, is rewarding . Using aThe studies described above focused on the perceptual dimensions underpinning social judgments of static, neutral faces ,2 and hoGiven the relationships between body perception, mate preferences, and intrasexual competitiveness, further research regarding the specific social perception of bodies and reward value is necessary. Consequently, the current study used PCAs of trait ratings of static, neutral bodies and a standard key-press task to investigate these issues. We also sought to replicate previous research reporting that social judgments of faces are underpinned by valence and dominance components ,2 and thStimuli were face and nude body images of 50 white men  and 50 white women . All images were taken from the 3d.sk image set.Face images were taken against neutral backgrounds. Individuals faced the camera with direct gaze and neutral expressions. Face images were aligned on pupil position and masked so only the face and ears were visible. Similar stimuli have been used in previous research on social perception of faces .Body images were also taken against neutral backgrounds. Individuals faced the camera with their legs shoulder width apart and arms at 45-degree angles. Bodies were standardized relative to actual height. Faces and genitals were obscured. Similar stimuli have been used in previous research on social perception of bodies ,10.These images were rated by 449 men  and 509 women  who were recruited online between October 2015 and November 2016. Raters provided written consent and the researchers did not have access to any identifying rater information. These raters were randomly assigned to rate the male faces, male bodies, female faces, or female bodies for one of the 13 traits previously investigated by Oosterhof and Todorov [https://osf.io/2j9qd/).The procedure for ratings of the 13 traits was based on that used by Oosterhof and Todorov . ParticiTwenty-six men  and 28 women  were recruited via email from October to November 2016 and provided written consent. Researchers did not have access to identifying participant information. Participants completed a standard key-press task, similar to those used to assess image reward value in previous research ,12. Resphttps://osf.io/g27wf/). Estimates of inter-rater agreement for each combination of trait and stimulus type, calculated using Cronbach’s alpha, are given in To investigate this issue, we first calculated the mean rating for every male face, male body, female face, and female body separately for each trait. All data and analysis scripts are also publically available  or the face dominance component . For female stimuli, the body general component was not correlated with the face valence component , the face dominance component , or the face geekiness component .We investigated this issue using linear mixed models. Analyses were conducted in the programming software R, version 3.4.0 in conjunction with lme4 and lmerTest ,14,15. BThe model for male faces showed significant positive effects of the male valence component  and the male dominance component . The interaction between participant sex and the male dominance component was also significant . The interaction between participant sex and the male dominance component reflected the positive effect of male dominance on key-press scores being stronger for female than male participants see . There wThe model for male bodies showed a significant positive effect of the male body general component . There were no other significant effects (both ps ≥ 0.062). The relationship between key-press scores and the male body general component is shown in The model for female faces showed a significant positive effect of the female valence component , a significant positive effect of the female dominance component , and a significant negative effect of the female geekiness component . There were no other significant effects . The relationships between key-press scores and the female valence, female dominance, and female geekiness components are shown in The model for female bodies showed a significant positive effect of the female body general component . There were no other significant effects (both ps ≥ 0.427). The relationship between key-press scores and the female body general component is shown in Key-press scores for faces and bodies were positively correlated for male stimuli , but not female stimuli .Our Principal Component Analyses (PCAs) of trait ratings of both male and female faces showed that much of the variance in social judgments of faces  was explained by two components: one that is highly correlated with traits such as trustworthiness and caringness  and the other that is highly correlated with traits such as dominance and aggressiveness (the dominance component). These results are very similar to those reported by Oosterhof and Todorov  and WangBy contrast with the results of our PCAs of trait ratings of face stimuli, much of the variance in social judgments of bodies  was explained by a single, general component that was highly correlated with attractiveness, dominance, and caringness. For both male and female stimuli, this body component was positively correlated with key-press scores. These results suggest that, by contrast with the reward value of static, neutral faces, the single general perceptual dimension, derived from trait ratings used here and in previous studies, predicts the reward value of static, neutral bodies. Thus, while there may be similarities in many aspects of observers’ responses to face and body stimuli ,20, our It is important to note that certain traits  were not included in body analyses because of their low inter-rater agreement, suggesting that these bodies may not provide information relevant to these trait judgements. Therefore, body perception may not be definable by the same intent and ability to cause harm  as face perception. The present analyses used established trait ratings relevant specifically to faces in order to determine whether the social perception of bodies followed the same pattern as faces and voices. Previous work has also used similar traits to determine that social perception of voices can be encapsulated by valence and dominance . In ordePrevious research reported that attractiveness ratings of nude bodies and faces were positively correlated ,10. ThatIn summary, we find that the reward value of faces is positively and independently correlated with perceptions of facial valence and dominance. By contrast, the reward value of bodies is positively correlated with a single, general perceptual component that reflects aspects of both the perceived valence and perceived dominance of bodies. These results highlight differences in how observers process faces and bodies.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.S5 Table(DOCX)Click here for additional data file.


The generation of Ca2+ signals is mostly attributed to Ca2+ release from internal Ca2+ stores evoked by an elevated metabotropic glutamate receptor (mGluR) activity. Different experimental results associated the generation of Ca2+ signals to the activity of the glutamate transporter (GluT). The GluT itself does not influence the intracellular Ca2+ concentration, but it indirectly activates Ca2+ entry over the membrane. A closer look into Ca2+ signaling in different astrocytic compartments revealed a spatial separation of those two pathways. Ca2+ signals in the soma are mainly generated by Ca2+ release from internal Ca2+ stores (mGluR-dependent pathway). In astrocytic compartments close to the synapse most Ca2+ signals are evoked by Ca2+ entry over the plasma membrane (GluT-dependent pathway). This assumption is supported by the finding, that the volume ratio between the internal Ca2+ store and the intracellular space decreases from the soma towards the synapse. We extended a model for mGluR-dependent Ca2+ signals in astrocytes with the GluT-dependent pathway. Additionally, we included the volume ratio between the internal Ca2+ store and the intracellular compartment into the model in order to analyze Ca2+ signals either in the soma or close to the synapse. Our model results confirm the spatial separation of the mGluR- and GluT-dependent pathways along the astrocytic process. The model allows to study the binary Ca2+ response during a block of either of both pathways. Moreover, the model contributes to a better understanding of the impact of channel densities on the interaction of both pathways and on the Ca2+ signal.Astrocytes integrate and process synaptic information and exhibit calcium (Ca 2+ signals in astrocytes. The functional role of astrocytic Ca2+ signals is still under debate. However, experimental results were able to show that astrocytic Ca2+ signaling acts to control local network activity, which plays an important role in diseases like epilepsy. Thus, it is of special interest to investigate the underlying mechanisms for Ca2+ signals in astrocytes in order to understand the role of astrocytes in neural network activity. Two different mechanisms are known to be responsible for the generation of Ca2+ signals in astrocytes. These mechanisms are the release of Ca2+ from internal Ca2+ stores and the entry of Ca2+ through the plasma membrane. We studied the interaction of those two different mechanisms for the generation of Ca2+ signals and found that these mechanisms are spatially separated along the astrocytic processes.Astrocytes are considered as active partners in neural information processing, because they integrate and process synaptic information and control synaptic transmission. Neuronal transmitter release induces the generation of Ca The maximal rate of IP3 production by PLCβ is described by vβ and the glutamate affinity of the receptor is set by KR. Kp is the Ca2+/PLC-dependent inhibition factor and Kπ determines the Ca2+ affinity of PLC.The production of IP3 production by PLCδ is described by vδ. The activity of PLCδ is inhibited according to the inhibition constant kδ. The Ca2+ affinity of PLCδ is set by KδPLC.The maximal rate of IP3 by IP3-3K is determined by v3K. KD is the Ca2+ affinity of IP3-3K and K3 is the IP3 affinity of IP3-3K.The maximal degradation rate of IP3 through dephosphorylation by the inositol polyphosphate 5-phosphatase (IP-5P) depends on the maximal rate, r5P, of degradation by IP-5P. Values of model parameters can be found in The degradation of IP2+ current through IP3 receptor channelsCa. The Ca2+ current through the IP3 receptor channel was taken from ER—[Ca2+]i). In order to relate the current strength to the volume of the intracellular space, the current is multiplied with the volume Vol. The current is normalized by the area A. Values of model parameters can be found in The probability of the channel to be in the open state is characterized by the term posed in  the chan3 receptor channelsActivation of IP. The fraction h of activated IP3 receptor channels was taken from i and is modeled by a Hill rate expression with an exponent 2. Values of model parameters can be found in The SERCA current depends on the intracellular Ca2+ leak from the ERCa. The Ca2+ leak from the endoplasmatic reticulum was taken from ER, and in the intracellular space [Ca2+]i. In order to relate the current strength to the volume of the intracellular space, the current is multiplied with the volume Vol. The current is normalized by the area A. Values of model parameters can be found in The leak of CaGlutamate transporter. The transport of glutamate mediated by the glutamate transporter (GluT) is determined by:GluTmax is the maximal transport current of the glutamate transporter. The half saturation constants of Na+, K+ and glutamate are given by KGluTmN, KGluTmK and KGluTmg, respectively. The half saturation constant of K+ is not known from experiments. Since the half saturation constant of Na+ is close to its intracellular resting concentration, we set the half saturation constant of K+ close to its extracellular resting concentration.+, one Glu- and one H+, and the counter-transport of one K+ i and the extracellular K+ concentration [K+]o [The Naon [K+]o . Values +/Ca2+ exchangerNa. The Na+/Ca2+ exchanger (NCX) mediates the exchange of three Na+ ions with one Ca2+ ion. We applied the mathematical description of the NCX of [NCXmax is the maximal pump current of the exchanger. The half saturation constants for Na+ and Ca2+ are given by KNCXmN and KNCXmC. The position of the energy barrier η controls the voltage dependence. ksat is a saturation factor ensuring saturation at large negative potentials.e NCX of :INCX=IN2+ is transported out of the astrocyte and Na+ is transported into the astrocyte. The reverse mode works the other way round. A switch into the reverse mode is induced by an increased intracellular Na+ concentration [+ and Ca2+ concentrations [Na+]i, [Na+]o, [Ca2+]i and [Ca2+]o. Values of model parameters can be found in The exchanger works either in the forward or in the reverse mode. In the forward mode Cantration . The curLeak currents. The leak currents of Na+ and K+ are given by:leakNa and gleakK are the corresponding conductances of the Na+ and K+ currents. The Nernst potentials of Na+ and K+ are ENa and EK. Values of model parameters can be found in τrec determines the recovery of these resources. The fraction of active synaptic resources y increases with each spike and the step increase of y is determined by U0. In the absence of a spike y decays back to a baseline level with time constant τfacil. The product r(t) corresponds to the ratio of glutamate (g) which is released during a spike of the sequence s. The change of the glutamate concentration in the synaptic cleft is determined by the total glutamate content of readily releasable vesicles (GT) and the volume ratio between the synaptic vesicles and the synaptic cleft (ρC). Glutamate is removed from the synaptic cleft with the time constant τclear. Values of model parameters can be found in The release of glutamate from an activated nearby synapse is calculated using the Tsodykis and Makram model , 22 in i3]i, the fraction h of active IP3 receptor channels, and [Ca2+]ER and the model parameters gNaleak and gKleak were determined as follows. Since the model parameters for the production and degradation of IP3 and the intracellular resting concentration of Ca2+ were known from literature, the zero of d[IP3]i/dt revealed the initial concentration of IP3. In the same way the initial ratio of activated IP3 receptor channels, h, and the initial concentration of the Ca2+ concentration in the endoplasmatic reticulum was calculated. In this way a stable resting state was ensured. The model parameter gNaleak was calculated by setting d[Na+]i/dt equal to zero and solving the equation for gNaleak. The model parameter gKleak was calculated the same way by setting d[K+]i/dt equal to zero.The initial values of i, the current strengths of the Na+/Ca2+ (INCX) and the IP3-receptor current (I3RIP) for different values of ImaxNCX and ratioER. After the application of a single action potential the Ca2+ concentration returned fastest to the resting concentration when the astrocytic compartment was devoid of the internal Ca2+ store (ratioER = 0) (see b). This process was slowed down by the Ca2+ transport mechanisms at the internal Ca2+ store (ratioER = 0.06 and 0.15). In general, the current strength of the Na+/Ca2+ exchanger reached the steady state much faster than the current strength of the IP3-receptor current . With an increase of the volume fraction of the internal Ca2+ store also the impact of the Ca2+ transport mechanisms at the endoplasmatic reticulum on the intracellular Ca2+ concentration increased. Thus, for larger values of ratioER it took longer for Ca2+ to return to its resting concentration.Time course of the intracellular Ca(EPS)Click here for additional data file.


Castration-resistant prostate cancer (CRPC) frequently develops after initial standard radiation and androgen deprivation therapy, leaving patients with limited further treatment options. Androgen receptor (AR) is a transcription factor that plays a key role in the initiation and progression of prostate cancer. p53, a major tumor suppressor that is rarely mutated in early-stages of prostate cancer, is often deregulated during prostate cancer progression. Here, we report an unusual co-amplification of MDM2 and MDMX, two crucial negative regulators of p53, in CRPC datasets. We demonstrate that combinatorial inhibition of MDM2 and MDMX, with nutlin-3 and NSC207895 respectively, has a profound inhibitory effect on cell proliferation of androgen-responsive, wild-type TP53 gene carrying prostate cancer cells LNCaP and 22Rv1. We further show that the combinatorial inhibition of MDM2 and MDMX not only activates p53, but also decreases cellular levels of AR and represses its function. Additionally, co-expression of MDM2 and MDMX stabilizes AR. Together, our results indicate that combinatorial inhibition of MDM2 and MDMX may offer a novel compelling strategy for prostate cancer therapy. Prostate cancer is the most common cancer in men . Since mmdm2 has been observed in more than 10% of human cancers and has been found sufficient to induce tumorigenesis [TP53 gene often remains wild-type in MDM2- or MDMX-overexpressing cancers, it has long been thought that targeting MDM2 or MDMX could restore p53 activity for cancer therapy [The tumor suppressor p53, the guardian of the genome, serves as one of the major cellular barriers against cancer development , 14. Theigenesis –22. MDMXigenesis . Althougigenesis , emerginigenesis –27. Overigenesis . Interesigenesis , suggest therapy , 30, 31. therapy –34. Addi therapy .TP53 gene. This combinatorial inhibition not only activates p53, but also decreases the cellular levels of AR and its function. Furthermore, we demonstrate that co-expression of MDM2 and MDMX leads to stabilization of AR, and that MDMX modulates the MDM2-mediated AR ubiquitination. Therefore, combinatorial inhibition of MDM2 and MDMX may offer a novel strategy for prostate cancer therapy by promoting the p53 function and repressing AR function.Here, we report an unusual co-amplification of MDM2 and MDMX in CRPC datasets. We show that nutlin-3 (an MDM2 inhibitor that disrupts the MDM2/p53 interaction) and NSC207895  co-treatment has a profound inhibitory effect on androgen-responsive prostate cancer LNCaP and 22RV1 cells that carry a wild-type copy of the TP53 gene [TP53 gene [cBioPortal. Our analysis of a CRPC dataset (Trento/Cornell/Broad 2016) revealed that MDMX is amplified in 32% of CRPC patients, compared to MDM2, which is amplified in 25% of CRPC patients  was identified through a high-throughput drug screening for compounds that could mitigate the MDMX promoter activity. NSC represses the MDMX promoter activity, resulting in decreased MDMX mRNA and protein expression, and reduced cell viability in MDMX amplified breast cancer cells . Furtherin vivo ubiquitination assay . We speculate the discrepancy between MDMX knock-down and NSC treatment may due to the fact that NSC treatment is more effective in reducing cellular levels of MDMX in comparison to MDMX siRNA treatment. As NSC structurally clustered with known DNA-damaging agents such as camptothecin , it may y Figure . Co-expry Figure  and 5D. LNCaP cells were grown in RPMI medium containing 10% fetal bovine serum (FBS) at 37°C. 22Rv1, DU145, and HEK293 cells were grown in Dulbecco modified Eagle medium containing 10% FBS at 37°C. Construction of Flag-MDM2 and HA-Ubiquitin was described previously , 60. pEGCommercially obtained antibodies were used to detect the following proteins or epitopes: androgen receptor , MDMX , actin , Flag , HA , and GFP . Mouse monoclonal antibodies against human p53 (DO-1) and MDM2  were used as supernatants from hybridoma cultures. Inhibitors used in this study were as follows: nutlin-3 , SJ172550 , RO5963 , NSC207895 , and MG132 .Transfections in HEK 293 were performed using PEI  with 1:3 ratio of DNA:PEI. In all transfection experiments, balancing amounts of empty vector (pcDNA3 plasmid) were added to ensure equal amounts of total DNA used for transfecting cells. Total cell lysates were prepared and separated on SDS polyacrylamide gels, transferred to nitrocellulose and immunoblotted with the indicated antibodies as described previously .® AQueous One Solution Cell Proliferation Assay . Approximately 3000 cells per well were plated in 96-well plates in 150 μl of complete medium  and allowed to attach for 20 hours under normal culture conditions. The cells in triplicates were treated with MDM2 or MDMX inhibitor alone or in combination, and incubated for 30 hours under normal culture conditions. Medium was then removed and replaced with 100 μl of fresh complete medium and 10 μl CellTiter 96® AQueous One Solution, and incubated for 2 hours at 37°C. The plates were read on an Emax Plus Microplate Reader (Molecular Devices) at a wavelength of 492 nm. The results are expressed as means ± s.d. of three independent experiments.Cell proliferation was measured by OD 492 nm using the CellTiter 96http://www.combosyn.com; [For synergistic analysis, LNCaP cells were treated with increasing dosages of nutlin-3 , NSC207895  or in combination as indicated for 30 hours and cell viability was measured. The absorbance at 492 nm of DMSO-treated cells was considered as 100% of survival (as 1 in the bar chart). The effects of drug treatment as fraction of DMSO-treated control cells were calculated. The dose-response values IC50 (dose required for median effect), m (slope signifying the shape of the dose–response curve) and r  for nutlin-3 and NSC were derived using Compusyn software  to visualize the cell viability. The crystal violet stained cells were scanned using LI-COR Odyssey CLx imaging system. The intensity of crystal violet signal in each well was quantified to represent the cell numbers in the well. The absorbance of DMSO treated cells was considered as 100%.1 × 10HEK293 cells were transfected with the indicated combinations of plasmids. Twenty-four hours after transfection, cells were treated with MG132 (20 μM) for 6 hours and then harvested. Total cell lysates were prepared and equal amounts of cleared cell lysates were subjected to anti-GFP  immunoprecipitation followed by western blotting with the monoclonal anti-HA antibody (Covance).Ct method (ΔΔCT method). The results are expressed as means ± s.d. of four experiments. Primer sequences are: PSA , TMPRSS2 , AR , p21 , PUMA , L32 , and p53 .LNCaP cells were plated in 6-well plates and treated with indicated combinations of MDM2 and MDMX inhibitors. Thirty hours after treatment, cells were harvested. RNA was extracted using a QIAGEN RNeasy mini-kit, and cDNA was synthesized with the QuantiTect reverse transcription kit (QIAGEN). Samples were analyzed by quantitative real-time PCR on a Bio-Rad CFX 96 using SYBR Green (Quantabio). RNA expression was normalized to RPL32 mRNA expression. Relative levels were calculated by the comparative cBioPortal. Copy number (aCGH) and gene expression data from a GEO publically available dataset , localized prostate cancers (N = 59), and metastatic CRPC samples (N = 35). The heatmap was generated using MeV software (http://mev.tm4.org).Prostate adenocarcinoma dataset  was anaSE35988; ) were ob