Identification of protein targets of nevirapine reactive metabolites using click chemistry and mass spectrometry-based differential proteomics

Abstract : Adverse drug reactions (ADRs) are undesirable effects caused after administration of a single dose or prolonged administration of drug or result from the combination of two or more drugs. Idiosyncratic drug reaction (IDR) is an adverse reaction that does not occur in most patients treated with a drug and does not involve the therapeutic effect of the drug. IDRs are unpredictable and often life-threatening. Idiosyncratic reaction is dependent on drug chemical characteristics or individual immunological response. IDRs are a major problem for drug development because they are usually not detected during clinical trials. In this study we focused on IDRs of Nevirapine (NVP), which is a non-nucleoside reverse transcriptase inhibitor used for the treatment of Human Immunodeficiency Virus (HIV) infections. The use of NVP is limited by a relatively high incidence of skin rash. NVP also causes a rash in female Brown Norway (BN) rats, which we use as animal model for this study. Our hypothesis is that idiosyncratic skin reactions associated with NVP treatment are due to post-translational modifications of proteins (e.g., glutathionylation) detectable by MS. The main objective of this study was to identify the proteins that are targeted by a reactive metabolite of Nevirapine in the skin. The specific objectives derived from the general objective were as follow: 1) To implement the click chemistry approach to detect proteins modified by a reactive NVP-Alkyne (NVP-ALK) metabolite. The purpose of using NVP-ALK was to couple it with Biotin using cycloaddition Click Chemistry reaction. 2) To detect protein modification using Western blotting and Mass Spectrometry techniques, which is important to understand the mechanism of NVP induced toxicity. 3) To identify the proteins using MASCOT search engine for protein identification, by comparing obtained spectrum from Mass Spectrometry with theoretical spectrum to find a matching peptide sequence. 4) To test if the drug or drug metabolites can cause harmful effects, as the induction of oxidative stress in cells (via protein glutathionylation). Oxidative stress causes cell damage that mediates signals, which likely induces the immune response. The results showed that Nevirapine is metabolized to a reactive metabolite, which causes protein modification. The extracted protein from the treated BN rats matched 10% of keratin, which implies that keratin was the protein targeted by the NVP-ALK.

A Belief rule-based environmental responsibility assessment system for small and medium-sized enterprises

Various environmental management systems, standards and tools are being created to assist companies to become more environmental friendly. However, not all the enterprises have adopted environmental policies in the same scale and range. Additionally, there is no existing guide to help them determine their level of environmental responsibility and subsequently, provide support to enable them to move forward towards environmental responsibility excellence. This research proposes the use of a Belief Rule-Based approach to assess an enterprise’s level commitment to environmental issues. The Environmental Responsibility BRB assessment system has been developed for this research. Participating companies will have to complete a structured questionnaire. An automated analysis of their responses (using the Belief Rule-Based approach) will determine their environmental responsibility level. This is followed by a recommendation on how to progress to the next level. The recommended best practices will help promote understanding, increase awareness, and make the organization greener. BRB systems consist of two parts: Knowledge Base and Inference Engine. The knowledge base in this research is constructed after an in-depth literature review, critical analyses of existing environmental performance assessment models and primarily guided by the EU Draft Background Report on "Best Environmental Management Practice in the Telecommunications and ICT Services Sector". The reasoning algorithm of a selected Drools JBoss BRB inference engine is forward chaining, where an inference starts iteratively searching for a pattern-match of the input and if-then clause. However, the forward chaining mechanism is not equipped with uncertainty handling. Therefore, a decision is made to deploy an evidential reasoning and forward chaining with a hybrid knowledge representation inference scheme to accommodate imprecision, ambiguity and fuzzy types of uncertainties. It is believed that such a system generates well balanced, sensible and Green ICT readiness adapted results, to help enterprises focus on making improvements on more sustainable business operations.

A Vision Based Target Detection System for Docking of an Autonomous Underwater Vehicle

This paper describes the development and preliminary experimental evaluation of a visionbased docking system to allow an Autonomous Underwater Vehicle (AUV) to identify and attach itself to a set of uniquely identifiable targets. These targets, docking poles, are detected using Haar rectangular features and rotation of integral images. A non-holonomic controller allows the Starbug AUV to orient itself with respect to the target whilst maintaining visual contact during the manoeuvre. Experimental results show the proposed vision system is capable of robustly identifying a pair of docking poles simultaneously in a variety of orientations and lighting conditions. Experiments in an outdoor pool show that this vision system enables the AUV to dock autonomously from a distance of up to 4m with relatively low visibility.

Determining the psychosocial predictors of living, living-related, and posthumous organ donation

The worldwide organ shortage occurs despite people’s positive organ donation attitudes. The discrepancy between attitudes and behaviour is evident in Australia particularly, with widespread public support for organ donation but low donation and communication rates. This problem is compounded further by the paucity of theoretically based research to improve our understanding of people’s organ donation decisions. This program of research contributes to our knowledge of individual decision making processes for three aspects of organ donation: (1) posthumous (upon death) donation, (2) living donation (to a known and unknown recipient), and (3) providing consent for donation by communicating donation wishes on an organ donor consent register (registering) and discussing the donation decision with significant others (discussing). The research program used extended versions of the Theory of Planned Behaviour (TPB) and the Prototype/Willingness Model (PWM), incorporating additional influences (moral norm, self-identity, organ recipient prototypes), to explicate the relationship between people’s positive attitudes and low rates of organ donation behaviours. Adopting the TPB and PWM (and their extensions) as a theoretical basis overcomes several key limitations of the extant organ donation literature including the often atheoretical nature of organ donation research, thefocus on individual difference factors to construct organ donor profiles and the omission of important psychosocial influences (e.g., control perceptions, moral values) that may impact on people’s decision-making in this context. In addition, the use of the TPB and PWM adds further to our understanding of the decision making process for communicating organ donation wishes. Specifically, the extent to which people’s registering and discussing decisions may be explained by a reasoned and/or a reactive decision making pathway is examined (Stage 3) with the novel application of the TPB augmented with the social reaction pathway in the PWM. This program of research was conducted in three discrete stages: a qualitative stage (Stage 1), a quantitative stage with extended models (Stage 2), and a quantitative stage with augmented models (Stage 3). The findings of the research program are reported in nine papers which are presented according to the three aspects of organ donation examined (posthumous donation, living donation, and providing consent for donation by registering or discussing the donation preference). Stage One of the research program comprised qualitative focus groups/interviews with university students and community members (N = 54) (Papers 1 and 2). Drawing broadly on the TPB framework (Paper 1), content analysed responses revealed people’s commonly held beliefs about the advantages and disadvantages (e.g., prolonging/saving life), important people or groups (e.g., family), and barriers and motivators (e.g., a family’s objection to donation), related to living and posthumous organ donation. Guided by a PWM perspective, Paper Two identified people’s commonly held perceptions of organ donors (e.g., altruistic and giving), non-donors (e.g., self-absorbed and unaware), and transplant recipients (e.g., unfortunate, and in some cases responsible/blameworthy for their predicament). Stage Two encompassed quantitative examinations of people’s decision makingfor living (Papers 3 and 4) and posthumous (Paper 5) organ donation, and for registering and discussing donation wishes (Papers 6 to 8) to test extensions to both the TPB and PWM. Comparisons of health students’ (N = 487) motivations and willingness for living related and anonymous donation (Paper 3) revealed that a person’s donor identity, attitude, past blood donation, and knowing a posthumous donor were four common determinants of willingness, with the results highlighting students’ identification as a living donor as an important motive. An extended PWM is presented in Papers Four and Five. University students’ (N = 284) willingness for living related and anonymous donation was tested in Paper Four with attitude, subjective norm, donor prototype similarity, and moral norm (but not donor prototype favourability) predicting students’ willingness to donate organs in both living situations. Students’ and community members’ (N = 471) posthumous organ donation willingness was assessed in Paper Five with attitude, subjective norm, past behaviour, moral norm, self-identity, and prior blood donation all significantly directly predicting posthumous donation willingness, with only an indirect role for organ donor prototype evaluations. The results of two studies examining people’s decisions to register and/or discuss their organ donation wishes are reported in Paper Six. People’s (N = 24) commonly held beliefs about communicating their organ donation wishes were explored initially in a TPB based qualitative elicitation study. The TPB belief determinants of intentions to register and discuss the donation preference were then assessed for people who had not previously communicated their donation wishes (N = 123). Behavioural and normative beliefs were important determinants of registering and discussing intentions; however, control beliefs influenced people’s registering intentions only. Paper Seven represented the first empirical test of the role of organ transplant recipient prototypes (i.e., perceptions of organ transplant recipients) in people’s (N = 465) decisions to register consent for organ donation. Two factors, Substance Use and Responsibility, were identified and Responsibility predicted people’s organ donor registration status. Results demonstrated that unregistered respondents were the most likely to evaluate transplant recipients negatively. Paper Eight established the role of organ donor prototype evaluations, within an extended TPB model, in predicting students’ and community members’ registering (n = 359) and discussing (n = 282) decisions. Results supported the utility of an extended TPB and suggested a role for donor prototype evaluations in predicting people’s discussing intentions only. Strong intentions to discuss donation wishes increased the likelihood that respondents reported discussing their decision 1-month later. Stage Three of the research program comprised an examination of augmented models (Paper 9). A test of the TPB augmented with elements from the social reaction pathway in the PWM, and extensions to these models was conducted to explore whether people’s registering (N = 339) and discussing (N = 315) decisions are explained via a reasoned (intention) and/or social reaction (willingness) pathway. Results suggested that people’s decisions to communicate their organ donation wishes may be better explained via the reasoned pathway, particularly for registering consent; however, discussing also involves reactive elements. Overall, the current research program represents an important step toward clarifying the relationship between people’s positive organ donation attitudes but low rates of organ donation and communication behaviours. Support has been demonstrated for the use of extensions to two complementary theories, the TPB and PWM, which can inform future research aiming to explicate further the organ donation attitude-behaviour relationship. The focus on a range of organ donation behaviours enables the identification of key targets for future interventions encouraging people’s posthumous and living donation decisions, and communication of their organ donation preference.

Condition-based prognosis of machine health

Modern machines are complex and often required to operate long hours to achieve production targets. The ability to detect symptoms of failure, hence, forecasting the remaining useful life of the machine is vital to prevent catastrophic failures. This is essential to reducing maintenance cost, operation downtime and safety hazard. Recent advances in condition monitoring technologies have given rise to a number of prognosis models that attempt to forecast machinery health based on either condition data or reliability data. In practice, failure condition trending data are seldom kept by industries and data that ended with a suspension are sometimes treated as failure data. This paper presents a novel approach of incorporating historical failure data and suspended condition trending data in the prognostic model. The proposed model consists of a FFNN whose training targets are asset survival probabilities estimated using a variation of Kaplan-Meier estimator and degradation-based failure PDF estimator. The output survival probabilities collectively form an estimated survival curve. The viability of the model was tested using a set of industry vibration data.

Adaptive depth estimation in image based visual servo control of dynamic systems

This paper considers the question of designing a fully image based visual servo control for a dynamic system. The work is motivated by the ongoing development of image based visual servo control of small aerial robotic vehicles. The observed targets considered are coloured blobs on a flat surface to which the normal direction is known. The theoretical framework is directly applicable to the case of markings on a horizontal floor or landing field. The image features used are a first order spherical moment for position and an image flow measurement for velocity. A fully non-linear adaptive control design is provided that ensures global stability of the closed-loop system. © 2005 IEEE.

Airborne vision-based collision-detection system

Machine vision represents a particularly attractive solution for sensing and detecting potential collision-course targets due to the relatively low cost, size, weight, and power requirements of vision sensors (as opposed to radar and TCAS). This paper describes the development and evaluation of a real-time vision-based collision detection system suitable for fixed-wing aerial robotics. Using two fixed-wing UAVs to recreate various collision-course scenarios, we were able to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. This type of image data is extremely scarce and was invaluable in evaluating the detection performance of two candidate target detection approaches. Based on the collected data, our detection approaches were able to detect targets at distances ranging from 400m to about 900m. These distances (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning of between 8-10 seconds ahead of impact, which approaches the 12.5 second response time recommended for human pilots. We overcame the challenge of achieving real-time computational speeds by exploiting the parallel processing architectures of graphics processing units found on commercially-off-the-shelf graphics devices. Our chosen GPU device suitable for integration onto UAV platforms can be expected to handle real-time processing of 1024 by 768 pixel image frames at a rate of approximately 30Hz. Flight trials using manned Cessna aircraft where all processing is performed onboard will be conducted in the near future, followed by further experiments with fully autonomous UAV platforms.

Personal epistemology in pre-service teachers : belief changes throughout a teacher education course

Classrooms of the 21st century are complex systems. They support diverse learners from varied contexts and function in a “messy” bricolage of policy contexts. This complexity is also evident in the nature of teaching and learning deployed in these classrooms. There is also, in current contexts, a general expectation that teachers will support students to construct, rather than simply receive knowledge. This process of constructing knowledge requires a focus on critical thinking in complex social and real world contexts (see also Elen & Clarebout, 2001; Yang, Chang & Hsu 2008). Critical thinking, which involves the identification and evaluation of multiple perspectives when making decisions, is a process of knowing – a tool of wisdom (Kuhn & Udell, 2001). Schommer-Aikens, Bird and Bakken (2010) refer to classrooms that encourage critical thinking as “epistemologically based” in which “the teacher encourages his/her students to look for connections among concepts within the text, with their prior knowledge, and with concepts found in the world beyond themselves” (p. 48).

A hidden Markov model and relative entropy rate approach to vision-based dim target detection for UAV sense-and-avoid

Uninhabited aerial vehicles (UAVs) are a cutting-edge technology that is at the forefront of aviation/aerospace research and development worldwide. Many consider their current military and defence applications as just a token of their enormous potential. Unlocking and fully exploiting this potential will see UAVs in a multitude of civilian applications and routinely operating alongside piloted aircraft. The key to realising the full potential of UAVs lies in addressing a host of regulatory, public relation, and technological challenges never encountered be- fore. Aircraft collision avoidance is considered to be one of the most important issues to be addressed, given its safety critical nature. The collision avoidance problem can be roughly organised into three areas: 1) Sense; 2) Detect; and 3) Avoid. Sensing is concerned with obtaining accurate and reliable information about other aircraft in the air; detection involves identifying potential collision threats based on available information; avoidance deals with the formulation and execution of appropriate manoeuvres to maintain safe separation. This thesis tackles the detection aspect of collision avoidance, via the development of a target detection algorithm that is capable of real-time operation onboard a UAV platform. One of the key challenges of the detection problem is the need to provide early warning. This translates to detecting potential threats whilst they are still far away, when their presence is likely to be obscured and hidden by noise. Another important consideration is the choice of sensors to capture target information, which has implications for the design and practical implementation of the detection algorithm. The main contributions of the thesis are: 1) the proposal of a dim target detection algorithm combining image morphology and hidden Markov model (HMM) filtering approaches; 2) the novel use of relative entropy rate (RER) concepts for HMM filter design; 3) the characterisation of algorithm detection performance based on simulated data as well as real in-flight target image data; and 4) the demonstration of the proposed algorithm's capacity for real-time target detection. We also consider the extension of HMM filtering techniques and the application of RER concepts for target heading angle estimation. In this thesis we propose a computer-vision based detection solution, due to the commercial-off-the-shelf (COTS) availability of camera hardware and the hardware's relatively low cost, power, and size requirements. The proposed target detection algorithm adopts a two-stage processing paradigm that begins with an image enhancement pre-processing stage followed by a track-before-detect (TBD) temporal processing stage that has been shown to be effective in dim target detection. We compare the performance of two candidate morphological filters for the image pre-processing stage, and propose a multiple hidden Markov model (MHMM) filter for the TBD temporal processing stage. The role of the morphological pre-processing stage is to exploit the spatial features of potential collision threats, while the MHMM filter serves to exploit the temporal characteristics or dynamics. The problem of optimising our proposed MHMM filter has been examined in detail. Our investigation has produced a novel design process for the MHMM filter that exploits information theory and entropy related concepts. The filter design process is posed as a mini-max optimisation problem based on a joint RER cost criterion. We provide proof that this joint RER cost criterion provides a bound on the conditional mean estimate (CME) performance of our MHMM filter, and this in turn establishes a strong theoretical basis connecting our filter design process to filter performance. Through this connection we can intelligently compare and optimise candidate filter models at the design stage, rather than having to resort to time consuming Monte Carlo simulations to gauge the relative performance of candidate designs. Moreover, the underlying entropy concepts are not constrained to any particular model type. This suggests that the RER concepts established here may be generalised to provide a useful design criterion for multiple model filtering approaches outside the class of HMM filters. In this thesis we also evaluate the performance of our proposed target detection algorithm under realistic operation conditions, and give consideration to the practical deployment of the detection algorithm onboard a UAV platform. Two fixed-wing UAVs were engaged to recreate various collision-course scenarios to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. Based on this collected data, our proposed detection approach was able to detect targets out to distances ranging from about 400m to 900m. These distances, (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning ahead of impact that approaches the 12.5 second response time recommended for human pilots. Furthermore, readily available graphic processing unit (GPU) based hardware is exploited for its parallel computing capabilities to demonstrate the practical feasibility of the proposed target detection algorithm. A prototype hardware-in- the-loop system has been found to be capable of achieving data processing rates sufficient for real-time operation. There is also scope for further improvement in performance through code optimisations. Overall, our proposed image-based target detection algorithm offers UAVs a cost-effective real-time target detection capability that is a step forward in ad- dressing the collision avoidance issue that is currently one of the most significant obstacles preventing widespread civilian applications of uninhabited aircraft. We also highlight that the algorithm development process has led to the discovery of a powerful multiple HMM filtering approach and a novel RER-based multiple filter design process. The utility of our multiple HMM filtering approach and RER concepts, however, extend beyond the target detection problem. This is demonstrated by our application of HMM filters and RER concepts to a heading angle estimation problem.

Towards the implementation of vision-based UAS sense-and-avoid

Machine vision represents a particularly attractive solution for sensing and detecting potential collision-course targets due to the relatively low cost, size, weight, and power requirements of the sensors involved. This paper describes the development of detection algorithms and the evaluation of a real-time flight ready hardware implementation of a vision-based collision detection system suitable for fixed-wing small/medium size UAS. In particular, this paper demonstrates the use of Hidden Markov filter to track and estimate the elevation (β) and bearing (α) of the target, compares several candidate graphic processing hardware choices, and proposes an image based visual servoing approach to achieve collision avoidance

Using ‘think aloud’ as a strategy for learning clinical reasoning in high fidelity case-based simulation for undergraduate nursing students

AIMS This paper reports on the implementation of a research project that trials an educational strategy implemented over six months of an undergraduate third year nursing curriculum. This project aims to explore the effectiveness of ‘think aloud’ as a strategy for learning clinical reasoning for students in simulated clinical settings. BACKGROUND Nurses are required to apply and utilise critical thinking skills to enable clinical reasoning and problem solving in the clinical setting [1]. Nursing students are expected to develop and display clinical reasoning skills in practice, but may struggle articulating reasons behind decisions about patient care. For students learning to manage complex clinical situations, teaching approaches are required that make these instinctive cognitive processes explicit and clear [2-5]. In line with professional expectations, nursing students in third year at Queensland University of Technology (QUT) are expected to display clinical reasoning skills in practice. This can be a complex proposition for students in practice situations, particularly as the degree of uncertainty or decision complexity increases [6-7]. The ‘think aloud’ approach is an innovative learning/teaching method which can create an environment suitable for developing clinical reasoning skills in students [4, 8]. This project aims to use the ‘think aloud’ strategy within a simulation context to provide a safe learning environment in which third year students are assisted to uncover cognitive approaches that best assist them to make effective patient care decisions, and improve their confidence, clinical reasoning and active critical reflection on their practice. MEHODS In semester 2 2011 at QUT, third year nursing students will undertake high fidelity simulation, some for the first time commencing in September of 2011. There will be two cohorts for strategy implementation (group 1= use think aloud as a strategy within the simulation, group 2= not given a specific strategy outside of nursing assessment frameworks) in relation to problem solving patient needs. Students will be briefed about the scenario, given a nursing handover, placed into a simulation group and an observer group, and the facilitator/teacher will run the simulation from a control room, and not have contact (as a ‘teacher’) with students during the simulation. Then debriefing will occur as a whole group outside of the simulation room where the session can be reviewed on screen. The think aloud strategy will be described to students in their pre-simulation briefing and allow for clarification of this strategy at this time. All other aspects of the simulations remain the same, (resources, suggested nursing assessment frameworks, simulation session duration, size of simulation teams, preparatory materials). RESULTS Methodology of the project and the challenges of implementation will be the focus of this presentation. This will include ethical considerations in designing the project, recruitment of students and implementation of a voluntary research project within a busy educational curriculum which in third year targets 669 students over two campuses. CONCLUSIONS In an environment of increasingly constrained clinical placement opportunities, exploration of alternate strategies to improve critical thinking skills and develop clinical reasoning and problem solving for nursing students is imperative in preparing nurses to respond to changing patient needs. References 1. Lasater, K., High-fidelity simulation and the development of clinical judgement: students' experiences. Journal of Nursing Education, 2007. 46(6): p. 269-276. 2. Lapkin, S., et al., Effectiveness of patient simulation manikins in teaching clinical reasoning skills to undergraduate nursing students: a systematic review. Clinical Simulation in Nursing, 2010. 6(6): p. e207-22. 3. Kaddoura, M.P.C.M.S.N.R.N., New Graduate Nurses' Perceptions of the Effects of Clinical Simulation on Their Critical Thinking, Learning, and Confidence. The Journal of Continuing Education in Nursing, 2010. 41(11): p. 506. 4. Banning, M., The think aloud approach as an educational tool to develop and assess clinical reasoning in undergraduate students. Nurse Education Today, 2008. 28: p. 8-14. 5. Porter-O'Grady, T., Profound change:21st century nursing. Nursing Outlook, 2001. 49(4): p. 182-186. 6. Andersson, A.K., M. Omberg, and M. Svedlund, Triage in the emergency department-a qualitative study of the factors which nurses consider when making decisions. Nursing in Critical Care, 2006. 11(3): p. 136-145. 7. O'Neill, E.S., N.M. Dluhy, and C. Chin, Modelling novice clinical reasoning for a computerized decision support system. Journal of Advanced Nursing, 2005. 49(1): p. 68-77. 8. Lee, J.E. and N. Ryan-Wenger, The "Think Aloud" seminar for teaching clinical reasoning: a case study of a child with pharyngitis. J Pediatr Health Care, 1997. 11(3): p. 101-10.

A process evaluation of a comprehensive school based injury prevention program

A process evaluation enables understanding of critical issues that can inform the improved, ongoing implementation of an intervention program. This study describes the process evaluation of a comprehensive, multi-level injury prevention program for adolescents. The program targets change in injury associated with violence, transport and alcohol risks and incorporates two primary elements: an 8-week, teacher delivered attitude and behaviour change curriculum for Grade 8 students; and a professional development program for teachers on school level methods of protection, focusing on strategies to increase students’ connectedness to school.

Public participation in infrastructure and construction projects in China: From an EIA-based to a whole-cycle process

Many governments world-wide are increasingly encouraging the involvement of interested individuals, groups and organisations in their publicinfrastructure and construction (PIC) projects as a means of improving the openness, transparency and accountability of the decision-making process and help improve the projects’ long-term viability and benefits to the community. In China, however, the current participatory mechanism at the project level exists only as part of the environmental impact assessment (EIA) process. With an increasing demand for PIC projects and social equality in China, this suggests a need to bring the participatory process into line with international practice. The aim of this paper, therefore, is to identify the weaknesses of EIA-basedpublicparticipation in China and the means by which it may be improved for the whole lifecycle of PIC schemes. To do this, the results of a series of interviews with a diverse group of experts is reported which analyse the nature and extent of existing problems of publicparticipation in EIA and suggestions for improvement. These indicate that the current level of participation in PIC projects is quite limited, particularly in the crucial earlier stages, primarily due to traditional culture and values, uneven progress in the adoption of participatory mechanisms, the risk of not meeting targets and lack of confidence in public competence. Finally, aprocess flowchart is proposed to guide construction practitioners and the community in general.

Private equity bidders : barbarians or best friends

The deal value of private equity merger and takeover activity has achieved unprecedented growth in the last couple of years, in Australia and globally. Private equity deals are not a new feature of the market; however, such deals have been subject to increased academic, professional and policy interest. This study examines the particular features of 15 major deals involving listed company "targets" and provides evidence – based on a comparison with a benchmark sample – to demonstrate the role that private equity plays in the market for corporate control. The objective of this study was to assess the friendliness of private equity bids. Based on the indicia compiled, lower bid premiums, the presence of break fees and the intention to retain senior management are compellingly different for private equity bids than for the comparative sample of bids. Using these several characteristics of "friendliness", the authors show that private equity deals are generally friendly in nature, consistent with industry rhetoric, but perhaps inconsistent with the popular belief that private equity bidders are the "barbarians at the gate".