CPU Activity Research Articles

Android-Based Power-Saving Framework for Mobile Devices Using the DEMATEL Method

Android-based power-saving framework" that is universally recognized. However, I can provide you with information about power-saving techniques and strategies commonly used in Android development up to that point. Keep in mind that developments might have occurred after September 2021. Android devices are known for their versatility and feature-rich environment, but this can come at the cost of increased power consumption. To mitigate this issue, developers and device manufacturers have employed various power-saving techniques and frameworks. Here are some common strategies and frameworks: Doze Mode and App Standby: Android introduced Doze Mode, which helps conserve battery life by delaying background CPU and network activity when a device is idle. App Standby takes this further by putting apps into a low-power state when they aren't actively used, reducing their impact on battery life. Background Execution Limits: Android limits background execution of apps to prevent unnecessary battery drain. Apps can only run background tasks within specific restrictions, ensuring that they don't continuously consume resources. JobScheduler: This framework allows apps to schedule tasks at optimal times, which can help consolidate tasks and reduce the frequency of waking up the device, thus saving power. Battery Optimization: Android provides a battery optimization feature that allows users to prioritize apps and restrict background activity for specific apps, helping to save power. Location Services: Managing location updates efficiently can significantly impact battery life. Using lower accuracy settings or batching location updates can reduce the power consumed by location services. Wakelocks and Alarms: Developers can use wakelocks and alarms to keep the device awake for specific tasks. However, these should be used judiciously, as they can lead to increased power consumption if not managed properly. Optimized Networking: Using techniques like Volley or OkHttp for efficient network requests, and optimizing the use of background data syncing, can help reduce power consumption. Background Syncing: DEMATEL is widely accepted for analyzing the overall relationship of factors and classifying factors into cause-and-effect types. Therefore, this article considers each source as a criterion in decision-making. To deal with a mixture of conflicting evidence, the significance and level of significance of each piece of evidence can be determined using DEMATEL; however, expanding the DEMATEL method with the source theory is required for better conclusions. Screen brightness & colour scheme, CPU frequency, Network, Low power localization and Wi-Fi. Rank using the DEMATEL for Android-based power-saving framework in Screen brightness & colour scheme is got the first rank whereas is the CPU frequency is having the Lowest rank.

Carboxypeptidase U (TAFIa) Is Rapidly Activated and Deactivated Following Thrombolysis and Thrombectomy in Stroke Patients.

The antifibrinolytic enzyme carboxypeptidase U (CPU, TAFIa, CPB2) is an appealing target for the treatment of acute ischemic stroke (AIS). Increased insights in CPU activation and inactivation during thrombolysis (rtPA) with or without endovascular thrombectomy (EVT) are required to develop CPU inhibitors as profibrinolytic agents with optimal benefits/risks. Therefore, CPU kinetics during ischemic stroke treatment were evaluated. AIS patients with documented cerebral artery occlusion receiving rtPA (N = 20) or rtPA + EVT (N = 16) were included. CPU activation during thrombolysis was measured by an ultrasensitive HPLC-based CPU activity method and by an ELISA measuring both CPU and inactivated CPU (CPU + CPUi). Intravenous blood samples were collected at admission and throughout the first 24h. Additional in situ blood samples were collected in the rtPA + EVT cohort proximal from the thrombus. The NIHSS score was determined at baseline and 24h. CPU activity and CPU + CPUi levels increased upon rtPA administration and reached peak values at the end of thrombolysis (1h). High inter-individual variability was observed in both groups. CPU activity decreased rapidly within 3h, while CPU + CPUi levels were still elevated at 7h. CPU activity or CPU + CPUi levels were similar in in situ and peripheral samples. No correlation between CPU or CPU + CPUi and NIHSS or thrombus localization was found. The CPU system was rapidly activated and deactivated following thrombolysis and thrombectomy in stroke patients, suggesting that a CPU inhibitor would have to be administered during rtPA infusion and over the next few hours. The high CPU generation variability suggests that some patients may not respond to the treatment. EudraCT number2017-002760-41.

Selective inhibition of carboxypeptidase U may reduce microvascular thrombosis in rat experimental stroke

BackgroundCarboxypeptidase U (CPU, CPB2, TAFIa) is a potent attenuator of fibrinolysis. The inhibition of CPU is thus an interesting strategy for improving thrombolysis. ObjectivesThe time course of CPU generation and proCPU consumption were assessed in an experimental rat model of acute ischemic stroke (AIS). In addition, the effects of the selective CPU inhibitor AZD9684 on CPU kinetics, microvascular thrombosis (MT), and AIS outcome were evaluated. MethodsRats were subjected to transient middle cerebral artery occlusion (tMCAO) and received recombinant tissue‐type plasminogen activator (tPA), a specific CPU inhibitor (AZD9684), combination therapy of tPA and AZD9684, or saline for 1 hour using a randomized treatment regime. CPU and proCPU levels were determined at five time points and assessed in light of outcome parameters (a.o.: infarct volume and fibrin[ogen] deposition as a measure for MT). ResultsClear activation of the CPU system was observed after AIS induction, in both saline‐ and tPA‐treated rats. Maximal CPU activities were observed at treatment cessation and were higher in tPA‐treated animals compared to the saline group. Concomitant proCPU consumption was more pronounced in tPA‐treated rats. AZD9684 suppressed the CPU activity and reduced fibrin(ogen) deposition, suggesting a reduction of MT. Nonetheless, a significant decrease in infarct volume was not observed. ConclusionsA pronounced activation of the CPU system was observed during tMCAO in rats. Selective inhibition of CPU with AZD9684 was able to reduce fibrin(ogen) deposition and brain edema, suggesting a reduction of MT but without a significant effect on final infarct volume.

Inhibition of the procarboxypeptidase U (proCPU, TAFI, proCPB2) system due to hemolysis

Spurious hemolysis of samples is the leading cause of interference in coagulation testing and was described to interfere in fibrinolysis assays. The influence of hemolysis on the procarboxypeptidase U (proCPU) system is not known. By means of spiking of hemolysate in pooled normal plasma, the effect of hemolysis on CPU, proCPU, and functional clot lysis assays was assessed. The influence of hemolysis on CPU generation during in vitro clot lysis was also evaluated. Cutoffs corresponding to maximal acceptable bias were determined. When active CPU was added to pooled plasma, a severe decrease in activity - up to 97.2% inhibition - was seen with increasing plasma concentrations of oxyhemoglobin (oxyHb) and the 10% cutoff value was found to be 0.3g/L oxyHb. Using an activity-based assay, proCPU levels appeared to decrease gradually with increased hemolysis (maximal reduction of 19.5%) with a 10% cutoff value of 4.2g/L oxyHb. The relative clot lysis time (CLT) showed a maximal negative bias of 68.5%. The reduction in CLT paralleled a significant reduction of the first CPU activity peak during clot lysis. The cutoff value for the CLT was 0.4g/L oxyHb. In presence of thrombomodulin (TM), CLT+TM was not affected up to 8.0g/L oxyHb. These data indicate a clear inhibition of the CPU system because of hemolysis resulting in an increase of lysis in functional fibrinolysis assays. We were able to quantify the inhibitory effect and to propose cutoff values for every parameter.

Leaky Noise: New Side-Channel Attack Vectors in Mixed-Signal IoT Devices

Microcontrollers and SoC devices have widely been used in Internet of Things applications. This also brings the question whether they lead to new security threats unseen in traditional computing systems. In fact, almost all modern SoC chips, particularly in the IoT domain, contain both analog and digital components, for various sensing and transmission tasks. Traditional remote-accessible online systems do not have this property, which can potentially become a security vulnerability. In this paper we demonstrate that such mixed-signal components, namely ADCs, expose a new security threat that allows attackers with ADC access to deduce the activity of a CPU in the system. To prove the leakage, we perform leakage assessment on three individual microcontrollers from two different vendors with various ADC settings. After showing a correlation of CPU activity with ADC noise, we continue with a leakage assessment of modular exponentiation and AES. It is shown that for all of these devices, leakage occurs for at least one algorithm and configuration of the ADC. Finally, we show a full key recovery attack on AES that works despite of the limited ADC sampling rate. These results imply that even remotely accessible microcontroller systems should be equipped with proper countermeasures against power analysis attacks, or restrict access to ADC data.

Adaptation to hardware variability for energy efficient use in the internet of things

Due to the evolution of silicon chips manufacturing processes at smaller and smaller nanoscales, the computing and memory substrates are increasingly changing, especially from an energy point of view. Considering projects with transistors composed of countable atoms quantities, small variations in the construction process can lead to energy costs of 10 times greater for the same processing. Software systems that identify hardware characteristics and take measures to adapt to the execution context amortize unnecessary energy expenditures. This economy is crucial for the execution continuity of embedded systems and/or applications used in the Internet of Things (IoT), where the energy resources are limited. One way to do this is by staggering tasks efficiently, postponing low-urgency services and running them all in only one period of CPU activity. The objective of this project was to increase the energy efficiency of IoT devices by creating a system that is capable of reorganizing and scheduling its tasks, as well as redistributing them in a network to be executed in nodes with characteristics of lower resource consumption.

Plasma carboxypeptidase U (CPU, CPB2, TAFIa) generation during in vitro clot lysis and its interplay between coagulation and fibrinolysis.

Carboxypeptidase U (CPU, CPB2, TAFIa) is a basic carboxypeptidase that is able to attenuate fibrinolysis. The inactive precursor procarboxypeptidase U is converted to its active form by thrombin, the thrombin-thrombomodulin complex or plasmin. The aim of this study was to investigate and characterise the time course of CPU generation in healthy individuals. In plasma of 29 healthy volunteers, CPU generation was monitored during in vitro clot lysis. CPU activity was measured by means of an enzymatic assay that uses the specific substrate Bz-o-cyano-Phe-Arg. An algorithm was written to plot the CPU generation curve and calculate the parameters that define it. In all individuals, CPU generation was biphasic. Marked inter-individual differences were present and a reference range was determined. The endogenous CPU generation potential is the composite effect of multiple factors. With respect to the first CPU activity peak characteristics, we found correlations with baseline proCPU concentration, proCPU Thr325Ile polymorphism, time to clot initiation and the clot lysis time. The second CPU peak related with baseline proCPU levels and with the maximum turbidity of the clot lysis profile. In conclusion, our method offers a technique to determine the endogenous CPU generation potential of an individual. The parameters obtained by the method quantitatively describe the different mechanisms that influence CPU generation during the complex interplay between coagulation and fibrinolysis, which are in line with the threshold hypothesis.

Accurate and Stable Run-Time Power Modeling for Mobile and Embedded CPUs

Modern mobile and embedded devices are required to be increasingly energy-efficient while running more sophisticated tasks, causing the CPU design to become more complex and employ more energy-saving techniques. This has created a greater need for fast and accurate power estimation frameworks for both run-time CPU energy management and design-space exploration. We present a statistically rigorous and novel methodology for building accurate run-time power models using performance monitoring counters (PMCs) for mobile and embedded devices, and demonstrate how our models make more efficient use of limited training data and better adapt to unseen scenarios by uniquely considering stability. Our robust model formulation reduces multicollinearity, allows separation of static and dynamic power, and allows a $100{\times }$ reduction in experiment time while sacrificing only 0.6% accuracy. We present a statistically detailed evaluation of our model, highlighting and addressing the problem of heteroscedasticity in power modeling. We present software implementing our methodology and build power models for ARM Cortex-A7 and Cortex-A15 CPUs, with 3.8% and 2.8% average error, respectively. We model the behavior of the nonideal CPU voltage regulator under dynamic CPU activity to improve modeling accuracy by up to 5.5% in situations where the voltage cannot be measured. To address the lack of research utilizing PMC data from real mobile devices, we also present our data acquisition method and experimental platform software. We support this paper with online resources including software tools, documentation, raw data and further results.

Plasma levels of carboxypeptidase U (CPU, CPB2 or TAFIa) are elevated in patients with acute myocardial infarction

Two decades after its discovery, carboxypeptidase U (CPU, CPB2 or TAFIa) has become a compelling drug target in thrombosis research. However, given the difficulty of measuring CPU in the blood circulation and the demanding sample collecton requirements, previous clinical studies focused mainly on measuring its inactive precursor, proCPU (proCPB2 or TAFI). Using a sensitive and specific enzymatic assay, we investigated plasma CPU levels in patients presenting with acute myocardial infarction (AMI) and in controls. In this case-control study, peripheral arterial blood samples were collected from 45 patients with AMI (25 with ST segment elevation myocardial infarction [STEMI], 20 with non-ST segment elevation myocardial infarction [NSTEMI]) and 42 controls. Additionally, intracoronary blood samples were collected from 11 STEMI patients during thrombus aspiration. Subsequently, proCPU and CPU plasma concentrations in all samples were measured by means of an activity-based assay, using Bz-o-cyano-Phe-Arg as a selective substrate. CPU activity levels were higher in patients with AMI (median LOD-LOQ, range 0-1277 mU L(-1) ) than in controls (median < LOD, range 0-128 mU L(-1) ). No correlation was found between CPU levels and AMI type (NSTEMI [median between LOD-LOQ, range 0-465 mU L(-1) ] vs. STEMI [median between LOD-LOQ, range 0-1277 mU L(-1) ]). Intracoronary samples (median 109 mU L(-1) , range 0-759 mU L(-1) ) contained higher CPU levels than did peripheral samples (median between LOD-LOQ, range 0-107 mU L(-1) ), indicating increased local CPU generation. With regard to proCPU, we found lower levels in AMI patients (median 910 U L(-1) , range 706-1224 U L(-1) ) than in controls (median 1010 U L(-1) , range 753-1396 U L(-1) ). AMI patients have higher plasma CPU levels and lower proCPU levels than controls. This finding indicates in vivo generation of functional active CPU in patients with AMI.

Constella: Crowdsourced system setting recommendations for mobile devices

The question “Where has my battery gone?” remains a common source of frustration for many smartphone users. With the increased complexity of smartphone applications, and the increasing number of system settings affecting them, understanding and optimizing battery use has become a difficult chore. The present paper develops a novel approach for constructing energy models from crowdsourced measurements. In contrast to previous approaches, which have focused on the effect of a specific sensor, system setting or application, our approach can simultaneously capture relationships between multiple factors, and provide a unified view of the energy state of the mobile device. We demonstrate the validity of using crowdsourced measurements for constructing battery models through a combination of large-scale analysis of a dataset containing battery discharge and system state measurements, and hardware power measurements. The results indicate that the models captured by our approach are both in line with previous studies on battery consumption and empirical measurements, providing a cost-effective way to construct energy models during normal operations of the device. The analysis also provides several new insights about battery consumption. For example, our analysis reveals the combined effect of high CPU activity and automatic screen brightness to be higher (resulting in 9 min shorter battery lifetime on average) than the effect of medium CPU load and manual screen brightness; a Wi-Fi signal strength drop of one bar can shorten battery life by over 13%; and a smartphone sitting in direct sunlight can witness over 50% shorter battery life than one indoors in cool conditions. Based on the crowdsourced energy models, we develop Constella, a novel recommender system for system settings. Constella provides actionable and human-readable recommendations on how to adjust system settings in order to reduce overall battery drain. We validate the effectiveness of Constella through a hardware power measurement experiment carried out using three application case studies. The results of the evaluation demonstrate that Constella is capable of generating recommendations that can provide up to 61% improvements in battery life.

LFDS: Scalable and High Performance Logging for Mission Critical Real Time Applications

In the world of connected enterprises and Internet of Things (IOT), millions of users and devices are connecting and transacting online simultaneously. Further, introduction of multi-core hardware platforms resulted in multi-fold increase in processing speed and volumes. To support the increasing volumes generated, building end-end-end scalable business applications has become the key focus of these service organizations. The reliability expectation of these systems is 100% and hence persisting of transaction information and key activities information is crucial to the success of the business applications. However, the performance of such software applications is inherently limited by disk input/output (I/O). Often, CPU activity gets suspended till I/O activity completes. Redesigning and tuning I/O can enhance application performance significantly. This paper presents our approach of ‘Log Flush Daemon Service’ (LFDS) in which application takes control of the I/O by taking it off the main transaction path along with hybrid of approaches from the techniques for optimization of the ancillary tasks of logging. This helps to enhance the performance, reduce the jitter and outliers.

Semantic multimedia remote display for mobile thin clients

Current remote display technologies for mobile thin clients convert practically all types of graphical content into sequences of images rendered by the client. Consequently, important information concerning the content semantics is lost. The present paper goes beyond this bottleneck by developing a semantic multimedia remote display. The principle consists of representing the graphical content as a real-time interactive multimedia scene graph. The underlying architecture features novel components for scene-graph creation and management, as well as for user interactivity handling. The experimental setup considers the Linux X windows system and BiFS/LASeR multimedia scene technologies on the server and client sides, respectively. The implemented solution was benchmarked against currently deployed solutions (VNC and Microsoft-RDP), by considering text editing and WWW browsing applications. The quantitative assessments demonstrate: (1) visual quality expressed by seven objective metrics, e.g., PSNR values between 30 and 42 dB or SSIM values larger than 0.9999; (2) downlink bandwidth gain factors ranging from 2 to 60; (3) real-time user event management expressed by network round-trip time reduction by factors of 4---6 and by uplink bandwidth gain factors from 3 to 10; (4) feasible CPU activity, larger than in the RDP case but reduced by a factor of 1.5 with respect to the VNC-HEXTILE.

Feasibility analysis and proof of concept for thermoelectric energy harvesting in mobile computers

Thermoelectric (TE) energy harvesting in compact microelectronic systems necessitates detailed upfront analysis to ensure unacceptable performance degradation is avoided. TE integration into a notebook computer is empirically investigated in this work for energy harvesting. A detailed finite element model was constructed first for thermal simulations. The model outputs were then correlated with the thermal validation results of the selected system. In parallel, a commercial TE micro-module was empirically characterized to quantify maximum power generation opportunity from the combined system and component data set. Next, suitable “warm spots” were identified within the mobile computer model to extract TE power with minimum or no notable impact to system performance, as measured by simulated thermal changes in the system. The prediction was validated by integrating a TE micro-module to the mobile system under test. Measured TE power generation density in the vicinity of the heat pipe was 1.26 mW/cm3 using high CPU load. The generated power scales down with lower CPU activity, and will scale up in proportion to the utilized opportunistic space within the system. The technical feasibility of TE energy harvesting in mobile computers has hence been experimentally proven for the first time.

Carboxypeptidase U (TAFIa) decreases the efficacy of thrombolytic therapy in ischemic stroke patients

Introduction Thrombolytic therapy improves clinical outcome in patients with acute ischemic stroke but is compromised by symptomatic intracranial hemorrhage and an unpredictable therapeutic response. In vitro and in vivo data suggest that activation of procarboxypeptidase U (proCPU) inhibits fibrinolysis. Aims To investigate whether the extent of proCPU activation is related to efficacy and safety of thrombolytic therapy in ischemic stroke patients. Methods In twelve patients with ischemic stroke who were treated with intravenous ( n = 7) or intra-arterial ( n = 5) thrombolysis, venous blood samples were taken at different time points before, during and after thrombolytic therapy. ProCPU and carboxypeptidase U (CPU, TAFIa) plasma concentrations were determined by HPLC. The maximal CPU activity (CPU max) and the percentage of proCPU consumption during thrombolytic therapy were calculated. The efficacy and safety of the thrombolytic therapy were assessed by evolution of the clinical deficit, recanalisation, final infarct volume, thrombolysis-induced intracranial hemorrhage and mortality. Results No correlations between CPU max or proCPU consumption and patient or stroke characteristics were found. However, CPU max is associated with evolution of the clinical deficit and achieved recanalisation. ProCPU consumption is related to the risk of intracranial hemorrhage, mortality and final infarct volume. Conclusions Irrespective of patient and stroke characteristics, CPU max and proCPU consumption during thrombolytic treatment for ischemic stroke are parameters for therapeutic efficacy and safety. Further evaluation of the clinical applicability of these parameters and further investigation of the potential role for CPU inhibitors as adjunctive therapeutics during thrombolytic treatment may be of value.

Discrete Event Modeling and Simulation of Wireless Sensor Network Performance

The wireless distributed microsensor networks have profited from recent technological advances and it seems essential to precisely understand these systems. Modeling and simulation appear to be an essential aspect of predicting the Wireless Sensor Network (WSN) specific behavior under different conditions. We want to provide a new method of modeling, simulation and visualization of WSN using a discrete-event approach. Described by Zeigler in the 1970's, the Discrete Event System Specification is ideal for describing the asynchronous nature of the events occuring in WSN. We have provided a basic model for the analysis of WSN performance, including routing management, energy consumption and relative CPU activity. Our approach uses a detailed definition of node-oriented components and aims to introduce methods of visualizing the network at a different level of abstraction.

Limited mutagenesis increases the stability of human carboxypeptidase U (TAFIa) and demonstrates the importance of CPU stability over proCPU concentration in down‐regulating fibrinolysis

Procarboxypeptidase U [proCPU, thrombin-activatable fibrinolysis inhibitor (TAFI), EC 3.4.17.20] belongs to the metallocarboxypeptidase family and is a zymogen found in human plasma. ProCPU has been proposed to be a molecular link between coagulation and fibrinolysis. Upon activation of proCPU, the active enzyme (CPU) rapidly becomes inactive due to its intrinsic instability. The inherent instability of CPU is likely to be of major importance for the in vivo down-regulation of its activity, but the underlying structural mechanisms of this fast and spontaneous loss of activity of CPU have not yet been explained, and they severely inhibit the structural characterization of CPU. In this study, we screened for more thermostable versions of CPU to increase our understanding of the mechanism underlying the instability of CPU's activity. We have shown that single as well as a few 2-4 mutations in human CPU can prolong the half-life of CPU's activity at 37 degrees C from 0.2 h of wild-type CPU to 0.5-5.5 h for the mutants. We provide evidence that the gain in stable activity is accompanied by a gain in thermostability of the enzyme and increased resistance to proteolytic digest by trypsin. Using one of the stable mutants, we demonstrate the importance of CPU stability over proCPU concentration in down-regulating fibrinolysis.

Uncertainty reduction techniques in microcontroller-based time measurements

This paper proposes and analyses different methods for reducing the uncertainty in microcontroller-based time measurements, which are increasingly common in interface circuits for sensors. The main uncertainty sources in these measurements are quantisation and trigger noise. The former depends on the technique used by the CPU for detecting the external events that start or stop the timing process, whereas the latter is in part attributable to the CPU activity. The sleep mode, a feature designed to reduce power consumption in microcontrollers, offers a simple and efficient solution to improve the measurement uncertainty because it reduces both the interrupt response time and the noise resulting from the CPU activity. These improvements are experimentally validated by testing an 8-bit microcontroller (AVR AT90S2313).

A Simple Cache Emulator for Evaluating Cache Behavior for SMP Systems

Every modern CPU uses a complex memory hierarchy, which consists of multiple cache memory levels. It is very difficult to predict the behavior of this hierarchy for a given program (for details see [1, 2]). The situation is even worse for systems with a shared memory. The most important example is the case of SMP (symmetric multiprocessing) systems [3]. The importance of these systems is growing due to the multi-core feature of the newest CPUs.The Cache Emulator (CE) can simulate the behavior of caches inside an SMP system and compute the number of cache misses during a computation. All measurements are done in the “off-line” mode on a single CPU. The CE uses its own emulated cache memory for an exact simulation. This means that no other CPU activity influences the behavior of the CE. This work extends the Cache Analyzer introduced in [4].

Inhibition of carboxypeptidase U (TAFIa) activity improves rt-PA induced thrombolysis in a dog model of coronary artery thrombosis

The objective of this study was to test the hypothesis if thrombolysis induced by recombinant tissue-type plasminogen activator, (rt-PA) could be facilitated by inhibiting carboxypeptidase U (CPU, active Thrombin Activatable Fibrinolysis Inhibitor, TAFIa) activity. The efficacy of rt-PA alone, or in combination with the carboxypeptidase inhibitor MERGETPA, was compared in a dog model of coronary artery thrombosis. Twenty dogs were randomised in two groups, one received rt-PA, 1 mg kg −1, as intravenous infusion over 20 min starting 30 min after thrombus formation, and the other group received rt-PA, 1 mg kg −1, as group one with the addition of MERGEPTA 5 mg kg −1 starting 25 min prior to coronary artery occlusion and followed by infusion of 5 mg kg −1 h −1 until the end of experiment. Efficacy was assessed by determination of time to lysis, duration of patency and blood flow during patency. Both groups had similar baseline characteristics with respect to haemodynamic parameters, i.e., heart rate, blood pressure and coronary artery blood flow. Coadministration of rt-PA and MERGETPA resulted in significant decrease in time to lysis (15±1.5 min vs. 20±1.7 min, p=0.03), increased patency time (87±16 min vs. 46±12 min, p=0.047) and increased coronary blood flow during patency (1131 mL h −1 vs. 405 mL h −1, p=0.015), compared to rt-PA alone. These results indicate that an inhibitor of CPU activity may have a beneficial effect in patients undergoing thrombolytic therapy by attaining shorter time to reperfusion and improved coronary patency.

Different mechanisms contribute to the biphasic pattern of carboxypeptidase U (TAFIa) generation during in vitro clot lysis in human plasma

Carboxypeptidase U (CPU,TAFIa) recently gained interest as a significant player in dampening the fibrinolytic rate. The aim of this study was to investigate the time course of the generation of CPU activity during coagulation and fibrinolysis using an in vitro clot lysis model in human plasma. A first peak of CPU activity appeared after initiation of the coagulation phase and a second rise in CPU activity was observed during the fibrinolysis. The decrease in the proCPU plasma concentration followed the same trend as the appearance of the CPU activity. The direct thrombin inhibitor inogatran eliminated the CPU generation during coagulation but not during fibrinolysis. Addition of the plasmin inhibitor aprotinin during fibrinolysis resulted in a decrease in CPU activation during the lysis phase. These results demonstrate that proCPU was activated during coagulation by thrombin and during fibrinolysis by plasmin. Addition of a CPU inhibitor before initiation of clotting decreased the clot lysis time as expected. However, addition in the time period between the two peaks of CPU activity had no apparent effect on the clot lysis time.