MDM2 Inhibitors for Cancer Therapy: The Past, Present, and Future.

Since its discovery over 35 years ago, MDM2 has emerged as an attractive target for the development of cancer therapy. MDM2's activities extend from carcinogenesis to immunity to the response to various cancer therapies. Since the report of the first MDM2 inhibitor more than 30 years ago, various approaches to inhibit MDM2 have been attempted, with hundreds of small-molecule inhibitors evaluated in preclinical studies and numerous molecules tested in clinical trials. Although many MDM2 inhibitors and degraders have been evaluated in clinical trials, there is currently no Food and Drug Administration (FDA)-approved MDM2 inhibitor on the market. Nevertheless, there are several current clinical trials of promising agents that may overcome the past failures, including agents granted FDA orphan drug or fast-track status. We herein summarize the research efforts to discover and develop MDM2 inhibitors, focusing on those that induce MDM2 degradation and exert anticancer activity, regardless of the p53 status of the cancer. We also describe how preclinical and clinical investigations have moved toward combining MDM2 inhibitors with other agents, including immune checkpoint inhibitors. Finally, we discuss the current challenges and future directions to accelerate the clinical application of MDM2 inhibitors. In conclusion, targeting MDM2 remains a promising treatment approach, and targeting MDM2 for protein degradation represents a novel strategy to downregulate MDM2 without the side effects of the existing agents blocking p53-MDM2 binding. Additional preclinical and clinical investigations are needed to finally realize the full potential of MDM2 inhibition in treating cancer and other chronic diseases where MDM2 has been implicated. SIGNIFICANCE STATEMENT: Overexpression/amplification of the MDM2 oncogene has been detected in various human cancers and is associated with disease progression, treatment resistance, and poor patient outcomes. This article reviews the previous, current, and emerging MDM2-targeted therapies and summarizes the preclinical and clinical studies combining MDM2 inhibitors with chemotherapy and immunotherapy regimens. The findings of these contemporary studies may lead to safer and more effective treatments for patients with cancers overexpressing MDM2.

Anticipatory information makes the difference: Behavioral effects and user assessments of a cyclist warning system to enhance cyclists' situation awareness.

PROBLEM: Increasing numbers of crashes involving pedelecs, and particularly older pedelec users, induce a need to enhance cycling safety. We evaluated a prototype cyclist warning system (CWS) that aims to increase situation awareness (SA) by alerting to safety critical events (SCE) with trimodal (auditory, visual, tactile). METHOD: To investigate the effects of CWS usage, we conducted a 2x2 mixed design bicycle simulator study with factors (1) CWS usage (within: rides WITH vs. WITHOUT CWS) and (2) age group (between: younger vs. older cyclists) on braking reaction time, gaze behavior, mental workload, and perceived safety. In sum, N = 64 participants (n = 32 younger, 18-40 years; n = 32 older, ≥ 55 years) took part in the study and experienced two balanced blocks of short rides including SCE of particular relevance for cycling safety. RESULTS: CWS usage resulted in earlier braking reactions to all investigated SCE and partly earlier fixation on the critical interaction partners (CIP) indicating increased cyclists' SA. Consistently to behavioral measures, participants' assessments regarding perceived safety further supported the safety improvements derived from CWS independently of age group. Moreover, CWS usage did not add to mental workload ratings. Age effects were selectively found for gaze data showing that across all SCE, older adults fixated longer and more frequently on street alignment, and less frequently on other road users. DISCUSSION: Taken together, the CWS evaluation showed promising results indicating the potential of the tested CWS to increase SA and enhance cyclists' safety both on a behavioral level and regarding subjective assessments. Further research should address the systems' safety potential under real-world conditions and for situations of higher complexity. PRACTICAL APPLICATIONS: Understanding the potential impact of road safety measures such as CWS is important to contribute effectively to reducing SCE.

Using event-related brain potentials to evaluate motor-auditory latencies in virtual reality.

Actions in the real world have immediate sensory consequences. Mimicking these in digital environments is within reach, but technical constraints usually impose a certain latency (delay) between user actions and system responses. It is important to assess the impact of this latency on the users, ideally with measurement techniques that do not interfere with their digital experience. One such unobtrusive technique is electroencephalography (EEG), which can capture the users' brain activity associated with motor responses and sensory events by extracting event-related potentials (ERPs) from the continuous EEG recording. Here we exploit the fact that the amplitude of sensory ERP components (specifically, N1 and P2) reflects the degree to which the sensory event was perceived as an expected consequence of an own action (self-generation effect). Participants (N = 24) elicit auditory events in a virtual-reality (VR) setting by entering codes on virtual keypads to open doors. In a within-participant design, the delay between user input and sound presentation is manipulated across blocks. Occasionally, the virtual keypad is operated by a simulated robot instead, yielding a control condition with externally generated sounds. Results show that N1 (but not P2) amplitude is reduced for self-generated relative to externally generated sounds, and P2 (but not N1) amplitude is modulated by delay of sound presentation in a graded manner. This dissociation between N1 and P2 effects maps back to basic research on self-generation of sounds. We suggest P2 amplitude as a candidate read-out to assess the quality and immersiveness of digital environments with respect to system latency.

Assessing mental workload with wearable devices - Reliability and applicability of heart rate and motion measurements.

Wearable devices are increasingly used for assessing physiological data. Industry 4.0 aims to achieve the real-time assessment of the workers' condition to adapt processes including the current mental workload. Mental workload can be assessed via physiological data. This paper researches the potential of wearable devices for mental workload assessment by utilizing heart rate and motion data collected with a smartwatch. A laboratory study was conducted with four levels of mental workload, ranging from none to high and during sitting and stepping activities. When sitting, a difference in the heart rate and motion data from the smartwatch was only found between no mental workload and any mental workload task. For the stepping condition, differences were found for the movement data. Based on these results, wearable devices could be useful in the future for detecting whether a mental demanding task is currently performed during low levels of physical activity.

The Effect of eHMI Malfunctions on Younger and Elderly Pedestrians' Trust and Acceptance of Automated Vehicle Communication Signals.

To ensure traffic flow and road safety in automated driving, external human-machine interfaces (eHMIs) could prospectively support the interaction between automated vehicles (AVs; SAE Level 3 or higher) and pedestrians if implicit communication is insufficient. Particularly elderly pedestrians (≥65 years) who are notably vulnerable in terms of traffic safety might benefit of the advantages of additional signals provided by eHMIs. Previous research showed that eHMIs were assessed as useful means of communication in AVs and were preferred over exclusively implicit communication signals. However, the attitudes of elderly users regarding technology usage and acceptance are ambiguous (i.e., less intention to use technology vs. a tendency toward overreliance on technology compared to younger users). Considering potential eHMI malfunctions, an appropriate level of trust in eHMIs is required to ensure traffic safety. So far, little research respected the impact of multiple eHMI malfunctions on participants' assessment of the system. Moreover, age effects were rarely investigated in eHMIs. In the current monitor-based study, N = 36 participants (19 younger, 17 elderly) repeatedly assessed an eHMI: During an initial measurement, when encountering a valid system and after experiencing eHMI malfunctions. Participants indicated their trust and acceptance in the eHMI, feeling of safety during the interaction and vigilance toward the eHMI. The results showed a positive effect of interacting with a valid system that acted consistently to the vehicle's movements compared to an initial assessment of the system. After experiencing eHMI malfunctions, participants' assessment of the system declined significantly. Moreover, elderly participants assessed the eHMI more positive across all conditions than younger participants did. The findings imply that participants considered the vehicle's movements as implicit communication cues in addition to the provided eHMI signals during the encounters. To support traffic safety and smooth interactions, eHMI signals are required to be in line with vehicle's movements as implicit communication cues. Moreover, the results underline the importance of calibrating an appropriate level of trust in eHMI signals. An adequate understanding of eHMI signals needs to be developed. Thereby, the requirements of different user groups should be specifically considered.

Effects of Gesture-Based Interaction on Driving Behavior: A Driving Simulator Study Using the Projection-Based Vehicle-in-the-Loop.

OBJECTIVE: We observe the driving performance effects of gesture-based interaction (GBI) versus touch-based interaction (TBI) for in-vehicle information systems (IVISs). BACKGROUND: As a contributing factor to a number of traffic accidents, driver distraction is a significant problem for traffic safety. More specifically, visual distraction has a strong negative impact on driving performance and risk perception. Thus, the implementation of new interaction systems that use midair gestures to encourage glance-free interactions could reduce visual distraction among drivers. METHODS: In this experiment, participants drove a projection-based Vehicle-in-the-Loop. The projection-based technology combines a visual simulation with kinesthetic, vestibular, and auditory feedback from a car on a test track. While driving, participants used GBI or TBI to perform IVIS tasks. To investigate driving behavior related to critical driving situations and car-following maneuvers, vehicle data based upon longitudinal and lateral driving were collected. RESULTS: Participants reacted faster to critical driving situations when using GBI compared to TBI. For drivers using TBI, steering performance decreased and time headway to a preceding vehicle was higher. CONCLUSION: Gestures provide a safe alternative to in-vehicle interactions. Moreover, GBI has fewer effects on driver distraction than TBI. APPLICATION: Potential applications of this research include all in-vehicle interaction systems used by drivers.

The box task - a method for assessing in-vehicle system demand.

The use of advanced in-vehicle information systems (IVIS) and other complex devices such as smartphones while driving can lead to driver distraction, which, in turn, increases safety-critical event risk. Therefore, using methods for measuring driver distraction caused by IVIS is crucial when developing new in-vehicle systems. In this paper, we present the setup and implementation of the Box Task combined with a Detection Response Task (BT+DRT) as a tool to assess visual-manual and cognitive distraction effects. The BT+DRT represents a low-cost and easy-to-use method which can be easily implemented by researchers in laboratory settings and which was validated in previous research. Moreover, at the end of this paper we describe the experimental procedure, the data analysis and discuss potential modifications of the method.•The setup and implementation of the Box Task combined with a Detection Response Task (BT+DRT) is described.•The method allows for measuring visual-manual and cognitive distraction of drivers.•The BT+DRT is a cost-effective and easy-to-use method that can be implemented in laboratory settings or driving simulators.

Information stored in memory affects abductive reasoning.

Abductive reasoning describes the process of deriving an explanation from given observations. The theory of abductive reasoning (TAR; Johnson and Krems, Cognitive Science 25:903-939, 2001) assumes that when information is presented sequentially, new information is integrated into a mental representation, a situation model, the central data structure on which all reasoning processes are based. Because working memory capacity is limited, the question arises how reasoning might change with the amount of information that has to be processed in memory. Thus, we conducted an experiment (N = 34) in which we manipulated whether previous observation information and previously found explanations had to be retrieved from memory or were still visually present. Our results provide evidence that people experience differences in task difficulty when more information has to be retrieved from memory. This is also evident in changes in the mental representation as reflected by eye tracking measures. However, no differences are found between groups in the reasoning outcome. These findings suggest that individuals construct their situation model from both information in memory as well as external memory stores. The complexity of the model depends on the task: when memory demands are high, only relevant information is included. With this compensation strategy, people are able to achieve similar reasoning outcomes even when faced with tasks that are more difficult. This implies that people are able to adapt their strategy to the task in order to keep their reasoning successful.

Memory-related cognitive load effects in an interrupted learning task: A model-based explanation.

BACKGROUND: The Cognitive Load Theory provides a well-established framework for investigating aspects of learning situations that demand learners' working memory resources. However, the interplay of these aspects at the cognitive and neural level is still not fully understood. METHOD: We developed four computational models in the cognitive architecture ACT-R to clarify underlying memory-related strategies and mechanisms. Our models account for human data of an experiment that required participants to perform a symbol sequence learning task with embedded interruptions. We explored the inclusion of subsymbolic mechanisms to explain these data and used our final model to generate fMRI predictions. RESULTS: The final model indicates a reasonable fit for reaction times and accuracy and links the fMRI predictions to the Cognitive Load Theory. CONCLUSIONS: Our work emphasizes the influence of task characteristics and supports a process-related view on cognitive load in instructional scenarios. It further contributes to the discussion of underlying mechanisms at a neural level.

Measuring driver distraction - Evaluation of the box task method as a tool for assessing in-vehicle system demand.

Several tools have been developed over the past twenty years to assess the degree of driver distraction caused by secondary task engagement. A relatively new and promising method in this area is the box task combined with a detection response task (BT + DRT). However, no evaluation regarding the BT's sensitivity currently exists. Thus, the aim of the present study was to evaluate the BT + DRT by comparing its sensitivity to the sensitivity of already established methods. Twenty-nine participants engaged in several artificial and realistic secondary tasks while either performing the BT + DRT, the Lane Change Test (LCT), or driving through a simple course in a simulator. The results showed that the BT parameters (especially the standard deviation of box position and size) were sensitive to differences in demand across the visual-manual secondary tasks. This was comparable to what was found with the LCT. Surprisingly, the BT performance measures were more sensitive than those of the driving simulation task. The BT + DRT also captured cognitive distraction effects with the integration of the DRT. Hence, the BT + DRT could be a cost-effective method to assess in-vehicle system demand. However, further investigations are necessary to better understand the potential of the BT method.

Using European naturalistic driving data to assess secondary task engagement when stopped at a red light.

PROBLEM: Some evidence exists that drivers choose to engage in secondary tasks when the driving demand is low (e.g., when the car is stopped). While such a behavior might generally be considered as rather safe, it could be argued that the associated diversion of attention away from the road still leads to a reduction of situational awareness, which might increase collision risk once the car regains motion. This is especially relevant for texting, which is associated with considerable eyes-off-the-road-time. Nonetheless, it seems that previous research has barely addressed the actual engagement in secondary tasks while waiting at a red light (as compared to just addressing the tasks' mere prevalence). OBJECTIVE: The present study investigated secondary task engagement while stopped at a red light using European naturalistic driving data collected through the UDRIVE project. Attention was given to the whole engagement process, including simple prevalence and the tasks' relation (in terms of start/end) to the red light period. Moreover, given that texting is one of the most problematic forms of distraction, it was characterized in more detail regarding glance behavior. METHOD: Videos of 804 red light episodes from 159 drivers were annotated. Glance behavior was also coded for a sub-set of 75 texting events and their matched baselines. Results, conclusions and practical applications: Drivers engaged in at least one secondary task across almost half of the annotated red light episodes. Drivers who texted while stopped spent most of the time looking at their cell phone. Consequently, drivers might not have been prepared for potentially unexpected events once the light turned green. Further, drivers concluded texting a considerable number of times well after the red light period, which has potential implications for traffic safety.

Tracing current explanations in memory: A process analysis based on eye-tracking.

Sequential abductive reasoning is the process of finding the best explanation for a set of observations. Explanations can be multicausal and require the retrieval of previously found ones from memory. The theory of abductive reasoning (TAR) allows detailed predictions on what information is stored and retrieved from memory during reasoning. In the research to date, however, these predictions have never been directly tested. In this study, we tested process assumptions such as the construction of a mental representation from TAR using memory indexing, an eye-tracking method that makes it possible to trace the retrieval of explanations currently held in working memory. Gaze analysis revealed that participants encode the presented evidence (i.e., observations) together with possible explanations into memory. When new observations are presented, the previously presented evidence and explanations are retrieved. Observations that are not explained immediately are encoded as abstractly explained. Abstract explanations enter a refinement process in which they become concrete before they enter the situation model. With the memory indexing method, we were able to assess the process of information retrieval in abductive reasoning, which was previously believed to be unobservable. We discuss the results in the light of TAR and other current theories on the diagnostic reasoning process.

Retinal safety evaluation of two-photon laser scanning in rats.

Safe use of retinal imaging with two-photon excitation in human eyes is crucial, as the effects of ultrashort pulsed lasers on the retina are relatively unknown. At the time of the study, the laser safety standards were inadequate due to the lack of biological data. This article addresses the feasibility of two-photon retinal imaging with respect to laser safety. In this study, rat retinas were evaluated at various laser exposure levels and with different laser parameters to determine the effects of laser-induced optical damage. The results were experimentally verified using confocal reflectance imaging, two-photon fluorescein angiography, immunohistochemistry, and correlated to the IEC 60825-1 laser safety standard.

Evaluation of Gesture-Based In-Vehicle Interaction: User Experience and the Potential to Reduce Driver Distraction.

OBJECTIVE: We observe the effects of in-vehicle system gesture-based interaction versus touch-based interaction on driver distraction and user experience. BACKGROUND: Driver distraction is a major problem for traffic safety, as it is a contributing factor to a number of accidents. Visual distraction in particular has a highly negative impact on the driver. One possibility for reducing visual driver distraction is to use new forms of interaction in the vehicle, such as gesture-based interaction. METHOD: In this experiment, participants drove on a motorway or in a city scenario while using touch-based interaction or gesture-based interaction. Subjective data, such as acceptance and workload, and objective data, including glance behavior, were gathered. RESULTS: As a result, participants rated their subjective impressions of safe driving as higher when using gesture-based interaction. More specifically, acceptance and attractiveness were higher, and workload was lower. The participants performed significantly fewer glances to the display and the glances were much shorter. CONCLUSION: Gestures are a positive alternative for in-vehicle interaction since effects on driver distraction are less significant when compared to touch-based interaction. APPLICATION: Potential application of this research includes interaction design of typical in-vehicle information and entertainment functions.

An experimental study to investigate design and assessment criteria: What is important for communication between pedestrians and automated vehicles?

In the near future, more vehicles will have automated functions. The traffic system will be a shared space of automated and manually driven vehicles. In our study we focused on the perspective of vulnerable road users, namely pedestrians, in cooperative situations with automated vehicles. Established communication methods, such as eye-contact between pedestrians and drivers, may no longer work when automated vehicles represent the interaction partner. Therefore, we evaluated several human-machine-interfaces (HMI) in order to implement smooth and comfortable communication. We conducted a two-stage study consisting of an explorative focus group discussion with naïve pedestrians (n = 6), followed by an experimental video simulation study (n = 25) based on the results of the focus group discussion. From the focus group we sought member opinion about various HMI, upon presentation of acoustic and visual communication systems such as projections, displays and LED light strips, in addition to portable communication systems, specifically smart watches. On the basis of the focus group discussion, an evaluation criteria was derived. For the video simulation study, HMI designs were created with variations in position, type and coding of the message, and technology. These were assessed by 25 subjects according to the focus discussion derived evaluation criteria: recognizability, unambiguousness, interaction comfort and intuitive comprehensibility. The results show that direct instructions to cross the street are preferred over status information of the vehicle and that large-scale text-based messages from the vehicle to the pedestrian, deliver better results. Design recommendations for HMIs for communication between automated vehicles are derived, and the extent external HMIs may supplement informal communication strategies such as vehicle movement or braking maneuvers, is discussed.

Regenerative braking failures in battery electric vehicles and their impact on the driver.

A unique feature of battery electric vehicles (BEV) is their regenerative braking system (RBS) to recapture kinetic energy in deceleration maneuvers. If such a system is triggered via gas pedal, most deceleration maneuvers can be executed by just using this pedal. This impacts the driving task as different deceleration strategies can be applied. Previous research has indicated that a RBS failure leading to a sudden reduced deceleration represents an adverse event for BEV drivers. In the present study, we investigated such a failure's impact on the driver's evaluation and behavior. We conducted an experiment on a closed-off test track using a modified BEV that could temporarily switch off the RBS. One half of the 44 participants in the study received information about an upcoming RBS failure whereas the other half did not. While 91% of the drivers receiving prior information noticed the RBS failure, only 48% recognized it in the "uniformed" group. In general, the failure and the perception of its occurrence influenced the driver's evaluation and behavior more than receiving prior information. Nevertheless, under the tested conditions, drivers kept control and were able to compensate for the RBS failure. As the participants drove quite simple maneuvers in our experiment, further studies are needed to validate our findings using more complex driving settings. Given that RBS failures could have severe consequences, appropriate information and warning strategies for drivers are necessary.

Chemically Active, Porous 3D-Printed Thermoplastic Composites.

Metal-organic frameworks (MOFs) exhibit exceptional properties and are widely investigated because of their structural and functional versatility relevant to catalysis, separations, and sensing applications. However, their commercial or large-scale application is often limited by their powder forms which make integration into devices challenging. Here, we report the production of MOF-thermoplastic polymer composites in well-defined and customizable forms and with complex internal structural features accessed via a standard three-dimensional (3D) printer. MOFs (zeolitic imidazolate framework; ZIF-8) were incorporated homogeneously into both poly(lactic acid) (PLA) and thermoplastic polyurethane (TPU) matrices at high loadings (up to 50% by mass), extruded into filaments, and utilized for on-demand access to 3D structures by fused deposition modeling. Printed, rigid PLA/MOF composites display a large surface area (SAavg = 531 m2 g-1) and hierarchical pore features, whereas flexible TPU/MOF composites achieve a high surface area (SAavg = 706 m2 g-1) by employing a simple method developed to expose obstructed micropores postprinting. Critically, embedded particles in the plastic matrices retain their ability to participate in chemical interactions characteristic of the parent framework. The fabrication strategies were extended to other MOFs and illustrate the potential of 3D printing to create unique porous and high surface area chemically active structures.

Driving comfort, enjoyment and acceptance of automated driving - effects of drivers' age and driving style familiarity.

Automated driving has the potential to improve the safety and efficiency of future traffic and to extend elderly peoples' driving life, provided it is perceived as comfortable and joyful and is accepted by drivers. Driving comfort could be enhanced by familiar automated driving styles based on drivers' manual driving styles. In a two-stage driving simulator study, effects of driving automation and driving style familiarity on driving comfort, enjoyment and system acceptance were examined. Twenty younger and 20 older drivers performed a manual and four automated drives of different driving style familiarity. Acceptance, comfort and enjoyment were assessed after driving with standardised questionnaires, discomfort during driving via handset control. Automation increased both age groups' comfort, but decreased younger drivers' enjoyment. Younger drivers showed higher comfort, enjoyment and acceptance with familiar automated driving styles, whereas older drivers preferred unfamiliar, automated driving styles tending to be faster than their age-affected manual driving styles. Practitioner Summary: Automated driving needs to be comfortable and enjoyable to be accepted by drivers, which could be enhanced by driving style individualisation. This approach was evaluated in a two-stage driving simulator study for different age groups. Younger drivers preferred familiar driving styles, whereas older drivers preferred driving styles unaffected by age.

In vivo two-photon imaging of retina in rabbits and rats.

The purpose of this study was to evaluate the retina using near-infrared (NIR) two-photon scanning laser ophthalmoscopy. New Zealand white rabbits, albino rats, and brown Norway rats were used in this study. An autofluorescence image of the retina, including the retinal cells and its associated vasculatures was obtained by a real-time scan using the ophthalmoscope. Furthermore, the retinal vessels, nerve fiber layers and the non-pigmented retina were recorded with two-photon fluorescein angiography (FA); and the choroidal vasculatures were recorded using two-photon indocyanine green angiography (ICGA). Two-photon ICGA was achieved by exciting a second singlet state at ∼398 nm. Simultaneous two-photon FA and two-photon ICGA were performed to characterize the retinal and choroidal vessels with a single injection. The minimum laser power threshold required to elicit two-photon fluorescence was determined. The two-photon ophthalmoscope could serve as a promising tool to detect and monitor the disease progression in animal models. Moreover, these high-resolution images of retinal and choroidal vessels can be acquired in a real-time scan with a single light source, requiring no additional filters for FA or ICGA. The combination of FA and ICGA using the two-photon ophthalmoscope will help researchers to characterize the retinal diseases in animal models, and also to classify the types (classic, occult or mixed) of choroidal neovascularization (CNV) in macular degeneration. Furthermore, the prototype can be adapted to image the retina of rodents and rabbits.

Bidirectional and Stretchable Piezoresistive Sensors Enabled by Multimaterial 3D Printing of Carbon Nanotube/Thermoplastic Polyurethane Nanocomposites.

Fabricating complex sensor platforms is still a challenge because conventional sensors are discrete, directional, and often not integrated within the system at the material level. Here, we report a facile method to fabricate bidirectional strain sensors through the integration of multiwalled carbon nanotubes (MWCNT) and multimaterial additive manufacturing. Thermoplastic polyurethane (TPU)/MWCNT filaments were first made using a two-step extrusion process. TPU as the platform and TPU/MWCNT as the conducting traces were then 3D printed in tandem using multimaterial fused filament fabrication to generate uniaxial and biaxial sensors with several conductive pattern designs. The sensors were subjected to a series of cyclic strain loads. The results revealed excellent piezoresistive responses with cyclic repeatability in both the axial and transverse directions and in response to strains as high as 50%. It was shown that the directional sensitivity could be tailored by the type of pattern design. A wearable glove, with built-in sensors, capable of measuring finger flexure was also successfully demonstrated where the sensors are an integral part of the system. These sensors have potential applications in wearable electronics, soft robotics, and prosthetics, where complex design, multi-directionality, embedding, and customizability are demanded.