The TAT-RasGAP317-326 anti-cancer peptide can kill in a caspase-, apoptosis-, and necroptosis-independent manner.

Tumor cell resistance to apoptosis, which is triggered by many anti-tumor therapies, remains a major clinical problem. Therefore, development of more efficient therapies is a priority to improve cancer prognosis. We have previously shown that a cell-permeable peptide derived from the p120 Ras GTPase-activating protein (RasGAP), called TAT-RasGAP317-326, bears anti-malignant activities in vitro and in vivo, such as inhibition of metastatic progression and tumor cell sensitization to cell death induced by various anti-cancer treatments. Recently, we discovered that this RasGAP-derived peptide possesses the ability to directly kill some cancer cells. TAT-RasGAP317-326 can cause cell death in a manner that can be either partially caspase-dependent or fully caspase-independent. Indeed, TAT-RasGAP317-326-induced toxicity was not or only partially prevented when apoptosis was inhibited. Moreover, blocking other forms of cell death, such as necroptosis, parthanatos, pyroptosis and autophagy did not hamper the killing activity of the peptide. The death induced by TAT-RasGAP317-326 can therefore proceed independently from these modes of death. Our finding has potentially interesting clinical relevance because activation of a death pathway that is distinct from apoptosis and necroptosis in tumor cells could lead to the generation of anti-cancer drugs that target pathways not yet considered for cancer treatment

It's (Not) Your Fault! Blame and Trust Repair in Human-Agent Cooperation

Buchholz V, Kulms P, Kopp S. It's (Not) Your Fault! Blame and Trust Repair in Human-Agent Cooperation. Kognitive Systeme. 2017;2017(1).In cooperative settings the success of the team is interlinked with the performance of the individual members. Thus, the possibility to address problems and mistakes of team members needs to be given. A common means in human-human interaction is the attribution of blame. Yet, it is not clear how blame attributions affect cooperation between humans and intelligent virtual agents and the overall perception of the agent. In order to take a first step in answering these questions, a study on cooperative human-agent interaction was conducted. The study was designed to investigate the effects of two different blaming strategies used by the agent in response to an alleged goal achievement failure, that is, self-blame (agent blames itself) followed by an apology versus other-blame (agent blames the user). The results indicate that the combination of blame and trust repair enables a successful continuation of the cooperation without loss of trust and likeability

Computational models of melanoma.

Genes, proteins, or cells influence each other and consequently create patterns, which can be increasingly better observed by experimental biology and medicine. Thereby, descriptive methods of statistics and bioinformatics sharpen and structure our perception. However, additionally considering the interconnectivity between biological elements promises a deeper and more coherent understanding of melanoma. For instance, integrative network-based tools and well-grounded inductive in silico research reveal disease mechanisms, stratify patients, and support treatment individualization. This review gives an overview of different modeling techniques beyond statistics, shows how different strategies align with the respective medical biology, and identifies possible areas of new computational melanoma research

Trust in interdependent and task-oriented human-computer cooperation

Kulms P. Trust in interdependent and task-oriented human-computer cooperation. Bielefeld: Universität Bielefeld; 2018.This thesis presents a new paradigm for the modeling of cooperative human–computer interaction in order to evaluate the antecedents, formation, and regulation of human–computer trust. Human–computer trust is the degree to which human users trust computers to help them achieve their goals, and functions as powerful psychological variable that governs user behavior. The modeling framework presented in this thesis aims to extend predominant methods for the study of trust and cooperation by building on competent problemsolving and equal goal contributions by users and computers. Specifically, the framework permits users to participate in interactive and interdependent decision-making games with autonomous computer agents. The main task is to solve a two-dimensional puzzle, similar to the popular game Tetris. The games derived from this framework include cooperative interaction factors known from interpersonal cooperation: the duality of competence and selfishness, anthropomorphism, task advice, and social blame. One validation study (68 participants) and four experiments (318 participants) investigate how these cooperative interaction factors influence human–computer trust. In particular, the results show how trust in computers is mediated by warmth as universal dimension of social cognition, how anthropomorphism of computers influences trust formation over time, and how expressive anthropomorphic cues can be used to regulate trust. We explain how these findings can be applied to design trustworthy computer agents for successful cooperation

Hand Movement Tracking Reveals Similar Processing of Anthropomorphic and Non-Anthropomorphic Cues During Attention Guiding

Kulms P, Kopp S. Hand Movement Tracking Reveals Similar Processing of Anthropomorphic and Non-Anthropomorphic Cues During Attention Guiding. Presented at the 49. Kongress der Deutschen Gesellschaft für Psychologie, Bochum

The effect of embodiment and competence on trust and cooperation in human-agent interaction

Kulms P, Kopp S. The effect of embodiment and competence on trust and cooperation in human-agent interaction. In: Intelligent Virtual Agents. 2016: 75-84

A social cognition perspective on human--computer trust. The effect of perceived warmth and competence on trust in decision-making with computers

Kulms P, Kopp S. A social cognition perspective on human--computer trust. The effect of perceived warmth and competence on trust in decision-making with computers. Frontiers in Digital Humanities. Human-Media Interaction. 2018;5: 14.Trust is a crucial guide in interpersonal interactions, helping people to navigate through social decision-making problems and cooperate with others. In human–computer interaction (HCI), trustworthy computer agents foster appropriate trust by supporting a match between their perceived and actual characteristics. As computers are increasingly endowed with capabilities for cooperation and intelligent problem-solving, it is critical to ask under which conditions people discern and distinguish trustworthy from untrustworthy technology. We present an interactive cooperation game framework allowing us to capture human social attributions that indicate trust in continued and interdependent human–agent cooperation. Within this framework, we experimentally examine the impact of two key dimensions of social cognition, warmth and competence, as antecedents of behavioral trust and self-reported trustworthiness attributions of intelligent computers. Our findings suggest that, first, people infer warmth attributions from unselfish vs. selfish behavior and competence attributions from competent vs. incompetent problem-solving. Second, warmth statistically mediates the relation between unselfishness and behavioral trust as well as between unselfishness and perceived trustworthiness. We discuss the possible role of human social cognition for human–computer trust

Molecular mechanisms of UV-induced apoptosis.

Sunburn cells, single standing cells with typical morphologic features occurring in UV-exposed skin, have been recognized as keratinocytes undergoing apoptosis following UV irradiation. Induction of apoptosis following UV exposure appears to be a protective mechanism, getting rid off severely damaged cells that bear the risk of malignant transformation. UV-mediated apoptosis is a highly complex process in which different molecular pathways are involved. These include DNA damage, activation of the tumor suppressor gene p53, triggering of cell death receptor