Humanoid facial expressions as a tool to study human behaviour

Besides action vitality forms, facial expressions represent another fundamental social cue which enables to infer the affective state of others. In the present study, we proposed the iCub robot as an interactive and controllable agent to investigate whether and how different facial expressions, associated to different action vitality forms, could modulate the motor behaviour of participants. To this purpose, we carried out a kinematic experiment in which 18 healthy participants observed video-clips of the iCub robot performing a rude or gentle request with a happy or angry facial expression. After this request, they were asked to grasp an object and pass it towards the iCub robot. Results showed that the iCub facial expressions significantly modulated participants motor response. Particularly, the observation of a happy facial expression, associated to a rude action, decreased specific kinematic parameters such as velocity, acceleration and maximum height of movement. In contrast, the observation of an angry facial expression, associated to a gentle action, increased the same kinematic parameters. Moreover, a behavioural study corroborated these findings, showing that the perception of the same action vitality form was modified when associated to a positive or negative facial expression.

Adverse effects of sodium-glucose cotransporter-2 inhibitors in patients with heart failure: a systematic review and meta-analysis

Sodium-glucose cotransoporter-2 inhibitors (SGLT-2Is) improve prognosis in heart failure (HF) patients both with reduced ejection fraction (HFrEF) and preserved ejection fraction (HFpEF). However, these drugs can have some side effects. To estimate the relative risk of side effects in HF patients treated with SGLT-2Is irrespective from left ventricular EF and setting (chronic and non-chronic HF). Five randomized controlled trials (RCTs) enrolling patients with HFrEF, 4 RCTs enrolling non-chronic HF, and 3 RCTs enrolling HFpEF were included. Among side effects, urinary infection, genital infection, acute kidney injury, diabetic ketoacidosis, hypoglycemia, hyperkalemia, hypokalemia, bone fractures, and amputations were considered in the analysis. Overall, 24,055 patients were included in the analysis: 9020 (38%) patients with HFrEF, 12,562 (52%) with HFpEF, and 2473 (10%) with non-chronic HF. There were no differences between SGLT-2Is and placebo in the risk to develop diabetic ketoacidosis, hypoglycemia, hyperkalemia, hypokalemia, bone fractures, and amputations. HFrEF patients treated with SGLT-2Is had a significant reduction of acute kidney injury (RR = 0.54 (95% CI 0.33-0.87), p = 0.011), whereas no differences have been reported in the HFpEF group (RR = 0.94 (95% CI 0.83-1.07), p = 0.348) and non-chronic HF setting (RR = 0.79 (95% CI 0.55-1.15), p = 0.214). A higher risk to develop genital infection (overall 2.57 (95% CI 1.82-3.63), p < 0.001) was found among patients treated with SGLT-2Is irrespective from EF (HFrEF: RR = 1.96 (95% CI 1.17-3.29), p = 0.011; HFpEF: RR = 3.04 (95% CI 1.88-4.90), p < 0.001). The risk to develop urinary infections was increased among SGLT-2I users in the overall population (RR = 1.13 (95% CI 1.00-1.28), p = 0.046) and in the HFpEF setting (RR = 1.19 (95% CI 1.02-1.38), p = 0.029), whereas no differences have been reported in HFrEF (RR = 1.05 (95% CI 0.81-1.36), p = 0.725) and in non-chronic HF setting (RR = 1.04 (95% CI 0.75-1.46), p = 0.806). SGLT-2Is increase the risk of urinary and genital infections in HF patients. In HFpEF patients, the treatment increases the risk of urinary infections compared to placebo, whereas SGLT-2Is reduce the risk of acute kidney disease in patients with HFrEF.

Remember me - user-centered implementation of working memory architectures on an industrial robot

The present research is innovative as we followed a user-centered approach to implement and train two working memory architectures on an industrial RB-KAIROS + robot: GRU, a state-of-the-art architecture, and WorkMATe, a biologically-inspired alternative. Although user-centered approaches are essential to create a comfortable and safe HRI, they are still rare in industrial settings. Closing this research gap, we conducted two online user studies with large heterogeneous samples. The major aim of these studies was to evaluate the RB-KAIROS + robot's appearance, movements, and perceived memory functions before (User Study 1) and after the implementation and training of robot working memory (User Study 2). In User Study 1, we furthermore explored participants' ideas about robot memory and what aspects of the robot's movements participants found positive and what aspects they would change. The effects of participants' demographic background and attitudes were controlled for. In User Study 1, participants' overall evaluations of the robot were moderate. Participant age and negative attitudes toward robots led to more negative robot evaluations. According to exploratory analyses, these effects were driven by perceived low experience with robots. Participants expressed clear ideas of robot memory and precise suggestions for a safe, efficient, and comfortable robot navigation which are valuable for further research and development. In User Study 2, the implementation of WorkMATe and GRU led to more positive evaluations of perceived robot memory, but not of robot appearance and movements. Participants' robot evaluations were driven by their positive views of robots. Our results demonstrate that considering potential users' views can greatly contribute to an efficient and positively perceived robot navigation, while users' experience with robots is crucial for a positive HRI.

Sacubitril/valsartan and arrhythmic burden in patients with heart failure and reduced ejection fraction: a systematic review and meta-analysis

The aim of this study was to assess whether angiotensin receptor/neprilysin inhibitor (ARNI) decreases ventricular arrhythmic burden compared to angiotensin-converting enzyme inhibitors or angiotensin receptor antagonist (ACE-I/ARB) treatment in chronic heart failure with reduced ejection fraction (HFrEF) patients. Further, we assessed if ARNI influenced the percentage of biventricular pacing. A systematic review of studies (both RCTs and observational studies) including HFrEF patients and those receiving ARNI after ACE-I/ARB treatment was conducted using Medline and Embase up to February 2023. Initial search found 617 articles. After duplicate removal and text check, 1 RCT and 3 non-RCTs with a total of 8837 patients were included in the final analysis. ARNI was associated with a significative reduction of ventricular arrhythmias both in RCT (RR 0.78 (95% CI 0.63-0.96); p = 0.02) and observational studies (RR 0.62; 95% CI 0.53-0.72; p < 0.001). Furthermore, in non-RCTs, ARNI also reduced sustained (RR 0.36 (95% CI 0.2-0.63); p < 0.001), non-sustained VT (RR 0.67 (95% CI 0.57-0.80; p = 0.007), ICD shock (RR 0.24 (95% CI 0.12-0.48; p < 0.001), and increased biventricular pacing (2.96% (95% CI 2.25-3.67), p < 0.001). In patients with chronic HFrEF, switching from ACE-I/ARB to ARNI treatment was associated with a consistent reduction of ventricular arrhythmic burden. This association could be related to a direct pharmacological effect of ARNI on cardiac remodeling.Trial registration: CRD42021257977.

Interactive Quantum Chemistry Enabled by Machine Learning, Graphical Processing Units, and Cloud Computing

Modern quantum chemistry algorithms are increasingly able to accurately predict molecular properties that are useful for chemists in research and education. Despite this progress, performing such calculations is currently unattainable to the wider chemistry community, as they often require domain expertise, computer programming skills, and powerful computer hardware. In this review, we outline methods to eliminate these barriers using cutting-edge technologies. We discuss the ingredients needed to create accessible platforms that can compute quantum chemistry properties in real time, including graphical processing units-accelerated quantum chemistry in the cloud, artificial intelligence-driven natural molecule input methods, and extended reality visualization. We end by highlighting a series of exciting applications that assemble these components to create uniquely interactive platforms for computing and visualizing spectra, 3D structures, molecular orbitals, and many other chemical properties. Expected final online publication date for the Annual Review of Physical Chemistry, Volume 74 is April 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Is It Me or the Robot? A Critical Evaluation of Human Affective State Recognition in a Cognitive Task

A key goal in human-robot interaction (HRI) is to design scenarios between humanoid robots and humans such that the interaction is perceived as collaborative and natural, yet safe and comfortable for the human. Human skills like verbal and non-verbal communication are essential elements as humans tend to attribute social behaviors to robots. However, aspects like the uncanny valley and different technical affinity levels can impede the success of HRI scenarios, which has consequences on the establishment of long-term interaction qualities like trust and rapport. In the present study, we investigate the impact of a humanoid robot on human emotional responses during the performance of a cognitively demanding task. We set up three different conditions for the robot with increasing levels of social cue expressions in a between-group study design. For the analysis of emotions, we consider the eye gaze behavior, arousal-valence for affective states, and the detection of action units. Our analysis reveals that the participants display a high tendency toward positive emotions in presence of a robot with clear social skills compared to other conditions, where we show how emotions occur only at task onset. Our study also shows how different expression levels influence the analysis of the robots' role in HRI. Finally, we critically discuss the current trend of automatized emotion or affective state recognition in HRI and demonstrate issues that have direct consequences on the interpretation and, therefore, claims about human emotions in HRI studies.

Human- or object-like? Cognitive anthropomorphism of humanoid robots

Across three experiments (N = 302), we explored whether people cognitively elaborate humanoid robots as human- or object-like. In doing so, we relied on the inversion paradigm, which is an experimental procedure extensively used by cognitive research to investigate the elaboration of social (vs. non-social) stimuli. Overall, mixed-model analyses revealed that full-bodies of humanoid robots were subjected to the inversion effect (body-inversion effect) and, thus, followed a configural processing similar to that activated for human beings. Such a pattern of finding emerged regardless of the similarity of the considered humanoid robots to human beings. That is, it occurred when considering bodies of humanoid robots with medium (Experiment 1), high and low (Experiment 2) levels of human likeness. Instead, Experiment 3 revealed that only faces of humanoid robots with high (vs. low) levels of human likeness were subjected to the inversion effects and, thus, cognitively anthropomorphized. Theoretical and practical implications of these findings for robotic and psychological research are discussed.

Perception is Only Real When Shared: A Mathematical Model for Collaborative Shared Perception in Human-Robot Interaction

Partners have to build a shared understanding of their environment in everyday collaborative tasks by aligning their perceptions and establishing a common ground. This is one of the aims of shared perception: revealing characteristics of the individual perception to others with whom we share the same environment. In this regard, social cognitive processes, such as joint attention and perspective-taking, form a shared perception. From a Human-Robot Interaction (HRI) perspective, robots would benefit from the ability to establish shared perception with humans and a common understanding of the environment with their partners. In this work, we wanted to assess whether a robot, considering the differences in perception between itself and its partner, could be more effective in its helping role and to what extent this improves task completion and the interaction experience. For this purpose, we designed a mathematical model for a collaborative shared perception that aims to maximise the collaborators’ knowledge of the environment when there are asymmetries in perception. Moreover, we instantiated and tested our model via a real HRI scenario. The experiment consisted of a cooperative game in which participants had to build towers of Lego bricks, while the robot took the role of a suggester. In particular, we conducted experiments using two different robot behaviours. In one condition, based on shared perception, the robot gave suggestions by considering the partners’ point of view and using its inference about their common ground to select the most informative hint. In the other condition, the robot just indicated the brick that would have yielded a higher score from its individual perspective. The adoption of shared perception in the selection of suggestions led to better performances in all the instances of the game where the visual information was not a priori common to both agents. However, the subjective evaluation of the robot’s behaviour did not change between conditions.

POST COVID-19 LUNG TRANSPLANTATION ITALIAN PIVOTAL PROTOCOL: SOME ETHICAL CONSIDERATIONS

SARS‑CoV‑2 mostly affects the respiratory system with clinical patterns ranging from the common cold to fatal pneumonia. During the first wave of the COVID-19 pandemic, owing to the high number of patients who were infected with SARS‑CoV‑2 and subsequently recovered, it has been shown that some patients with post–COVID-19 terminal respiratory failure need lung transplantation for survival. There is increasing evidence coming from worldwide observations that this procedure can be performed successfully in post–COVID-19 patients. However, owing to the scarcity of organs, there is a need to define the safety and efficacy of lung transplant for post–COVID-19 patients as compared to patients waiting for a lung transplant for other pre-existing conditions, in order to ensure that sound ethical criteria are applied in organ allocation. The Milan's Policlinic Lung Transplant Surgery Unit, with the revision of the National Second Opinion for Infectious Diseases and the contribution of the Italian Lung Transplant Centres and the Italian National Transplant Centre, set up a pivotal observational protocol for the lung transplant of patients infected and successively turned negative for SARS‑CoV‑2, albeit with lung consequences such as acute respiratory distress syndrome or some chronic interstitial lung disease.

The protocol was revised and approved by the Italian National Institute of Health Ethics Committee. Description of the protocol and some ethical considerations are reported in this article.

A Case of Prolonged Hospital Acquired COVID-19 Pneumonia in a Lung Transplant Recipient: Management and Outcome

Introduction

Lung transplant recipients are at increased risk of SARS-CoV2 infection due to immunosuppression and their management has yet to be standardized. We report a case of prolonged COVID-19 infection in a lung recipient acquired after transplant during the hospital stay.

Case Report

A 52-year-old lady with interstitial disease associated to systemic sclerosis underwent bilateral lung transplantation on 04/10/21. Donors and recipient microbiological tests for SARS-CoV2 were negative on molecular swabs performed before transplantation (04/07 and 04/10). Transplantation was uneventful and the recipient was extubated the subsequent day. Twelve days later, a surveillance molecular nose-pharyngeal swab was positive for SARS-CoV2. The positivity for subgenomic analysis revealed productive infection. At first monitoring biopsy, multiple foci of diffuse alveolar damage, significant cytopathic features of pneumocytes, microthrombi of capillaries, and extensive edema were highly suggestive of COVID-19 pneumonia. High viral load was also detected in lung biopsy by RT-PCR. She presented mild respiratory symptoms (cough with low oxygen supplementation) and the CT scan revealed an area of consolidation at the right lower lobe. Monoclonal antibody therapy (Bamlanivimab and Etesevimab) associated with remdesevir was started, IV immunoglobulins were administered while mycophenolate mofetil was discontinued. The patient was closely monitored until the nose-pharyngeal swab turned negative two months after the first positivity associated with a significant clinical improvement. At the last follow-up, five months after transplantation, she had good pulmonary function, no immunological disorders and no signs related to long COVID-19.

Summary

This is a case of prolonged hospital acquired COVID-19 related pneumonia in a lung recipient. Immunocompromized patients present a longer viral clearance. In this fragile population a strict clinical, radiological and histopathological monitoring associated with encouragement of vaccination are mandatory.

A Humanoid Robot’s Effortful Adaptation Boosts Partners’ Commitment to an Interactive Teaching Task

We tested the hypothesis that, if a robot apparently invests effort in teaching a new skill to a human participant, the human participant will reciprocate by investing more effort in teaching the robot a new skill, too. To this end, we devised a scenario in which the iCub and a human participant alternated in teaching each other new skills. In the Adaptive condition of the robot teaching phase , the iCub slowed down its movements when repeating a demonstration for the human learner, whereas in the Unadaptive condition it sped the movements up when repeating the demonstration. In a subsequent participant teaching phase , human participants were asked to give the iCub a demonstration, and then to repeat it if the iCub had not understood. We predicted that in the Adaptive condition , participants would reciprocate the iCub’s adaptivity by investing more effort to slow down their movements and to increase segmentation when repeating their demonstration. The results showed that this was true when participants experienced the Adaptive condition after the Unadaptive condition and not when the order was inverted, indicating that participants were particularly sensitive to the changes in the iCub’s level of commitment over the course of the experiment.

A Biological Inspired Cognitive Framework for Memory-Based Multi-Sensory Joint Attention in Human-Robot Interactive Tasks

One of the fundamental prerequisites for effective collaborations between interactive partners is the mutual sharing of the attentional focus on the same perceptual events. This is referred to as joint attention. In psychological, cognitive, and social sciences, its defining elements have been widely pinpointed. Also the field of human-robot interaction has extensively exploited joint attention which has been identified as a fundamental prerequisite for proficient human-robot collaborations. However, joint attention between robots and human partners is often encoded in prefixed robot behaviours that do not fully address the dynamics of interactive scenarios. We provide autonomous attentional behaviour for robotics based on a multi-sensory perception that robustly relocates the focus of attention on the same targets the human partner attends. Further, we investigated how such joint attention between a human and a robot partner improved with a new biologically-inspired memory-based attention component. We assessed the model with the humanoid robot iCub involved in performing a joint task with a human partner in a real-world unstructured scenario. The model showed a robust performance on capturing the stimulation, making a localisation decision in the right time frame, and then executing the right action. We then compared the attention performance of the robot against the human performance when stimulated from the same source across different modalities (audio-visual and audio only). The comparison showed that the model is behaving with temporal dynamics compatible with those of humans. This provides an effective solution for memory-based joint attention in real-world unstructured environments. Further, we analyzed the localisation performances (reaction time and accuracy), the results showed that the robot performed better in an audio-visual condition than an audio only condition. The performance of the robot in the audio-visual condition was relatively comparable with the behaviour of the human participants whereas it was less efficient in audio-only localisation. After a detailed analysis of the internal components of the architecture, we conclude that the differences in performance are due to egonoise which significantly affects the audio-only localisation performance.

The influence of vitality forms on action perception and motor response

During the interaction with others, action, speech, and touches can communicate positive, neutral, or negative attitudes. Offering an apple can be gentle or rude, a caress can be kind or rushed. These subtle aspects of social communication have been named vitality forms by Daniel Stern. Although they characterize all human interactions, to date it is not clear whether vitality forms expressed by an agent may affect the action perception and the motor response of the receiver. To this purpose, we carried out a psychophysics study aiming to investigate how perceiving different vitality forms can influence cognitive and motor tasks performed by participants. In particular, participants were stimulated with requests made through a physical contact or vocally and conveying rude or gentle vitality forms, and then they were asked to estimate the end of a passing action observed in a monitor (action estimation task) or to perform an action in front of it (action execution task) with the intention to pass an object to the other person presented in the video. Results of the action estimation task indicated that the perception of a gentle request increased the duration of a rude action subsequently observed, while the perception of a rude request decreased the duration of the same action performed gently. Additionally, during the action execution task, accordingly with the perceived vitality form, participants modulated their motor response.

Machines Like Us and People Like You: Toward Human-Robot Shared Experience

In the past years, the field of collaborative robots has been developing fast, with applications ranging from health care to search and rescue, construction, entertainment, sports, and many others. However, current social robotics is still far from the general abilities we expect in a robot collaborator. This limitation is more evident when robots are faced with real-life contexts and activities occurring over long periods. In this article, we argue that human-robot collaboration is more than just being able to work side by side on complementary tasks: collaboration is a complex relational process that entails mutual understanding and reciprocal adaptation. Drawing on this assumption, we propose to shift the focus from "human-robot interaction" to "human-robot shared experience." We hold that for enabling the emergence of such shared experiential space between humans and robots, constructs such as coadaptation, intersubjectivity, individual differences, and identity should become the central focus of modeling. Finally, we suggest that this shift in perspective would imply changing current mainstream design approaches, which are mainly focused on functional aspects of the human-robot interaction, to the development of architectural frameworks that integrate the enabling dimensions of social cognition.

Crocetin Mitigates Irradiation Injury in an In Vitro Model of the Pubertal Testis: Focus on Biological Effects and Molecular Mechanisms

Infertility is a potential side effect of radiotherapy and significantly affects the quality of life for adolescent cancer survivors. Very few studies have addressed in pubertal models the mechanistic events that could be targeted to provide protection from gonadotoxicity and data on potential radioprotective treatments in this peculiar period of life are elusive. In this study, we utilized an in vitro model of the mouse pubertal testis to investigate the efficacy of crocetin to counteract ionizing radiation (IR)-induced injury and potential underlying mechanisms. Present experiments provide evidence that exposure of testis fragments from pubertal mice to 2 Gy X-rays induced extensive structural and cellular damage associated with overexpression of PARP1, PCNA, SOD2 and HuR and decreased levels of SIRT1 and catalase. A twenty-four hr exposure to 50 μM crocetin pre- and post-IR significantly reduced testis injury and modulated the response to DNA damage and oxidative stress. Nevertheless, crocetin treatment did not counteract the radiation-induced changes in the expression of SIRT1, p62 and LC3II. These results increase the knowledge of mechanisms underlying radiation damage in pubertal testis and establish the use of crocetin as a fertoprotective agent against IR deleterious effects in pubertal period.

Speech Envelope Dynamics for Noise-Robust Auditory Scene Analysis in Robotics

Humans make extensive use of auditory cues to interact with other humans, especially in challenging real-world acoustic environments. Multiple distinct acoustic events usually mix together in a complex auditory scene. The ability to separate and localize mixed sound in complex auditory scenes remains a demanding skill for binaural robots. In fact, binaural robots are required to disambiguate and interpret the environmental scene with only two sensors. At the same time, robots that interact with humans should be able to gain insights about the speakers in the environment, such as how many speakers are present and where they are located. For this reason, the speech signal is distinctly important among auditory stimuli commonly found in human-centered acoustic environments. In this paper, we propose a Bayesian method of selectively processing acoustic data that exploits the characteristic amplitude envelope dynamics of human speech to infer the location of speakers in the complex auditory scene. The goal was to demonstrate the effectiveness of this speech-specific temporal dynamics approach. Further, we measure how effective this method is in comparison with more traditional methods based on amplitude detection only.

A Socially Adaptable Framework for Human-Robot Interaction

In our everyday lives we regularly engage in complex, personalized, and adaptive interactions with our peers. To recreate the same kind of rich, human-like interactions, a social robot should be aware of our needs and affective states and continuously adapt its behavior to them. Our proposed solution is to have the robot learn how to select the behaviors that would maximize the pleasantness of the interaction for its peers. To make the robot autonomous in its decision making, this process could be guided by an internal motivation system. We wish to investigate how an adaptive robotic framework of this kind would function and personalize to different users. We also wish to explore whether the adaptability and personalization would bring any additional richness to the human-robot interaction (HRI), or whether it would instead bring uncertainty and unpredictability that would not be accepted by the robot's human peers. To this end, we designed a socially adaptive framework for the humanoid robot iCub. As a result, the robot perceives and reuses the affective and interactive signals from the person as input for the adaptation based on internal social motivation. We strive to investigate the value of the generated adaptation in our framework in the context of HRI. In particular, we compare how users will experience interaction with an adaptive versus a non-adaptive social robot. To address these questions, we propose a comparative interaction study with iCub whereby users act as the robot's caretaker, and iCub's social adaptation is guided by an internal comfort level that varies with the stimuli that iCub receives from its caretaker. We investigate and compare how iCub's internal dynamics would be perceived by people, both in a condition when iCub does not personalize its behavior to the person, and in a condition where it is instead adaptive. Finally, we establish the potential benefits that an adaptive framework could bring to the context of repeated interactions with a humanoid robot.

How attitudes generated by humanoid robots shape human brain activity

During interpersonal interactions, people perform actions with different forms of vitality, communicating their positive or negative attitude toward others. For example, a handshake can be "soft" or "vigorous", a caress can be 'kind' or 'rushed'. While previous studies have shown that the dorso-central insula is a key area for the processing of human vitality forms, there is no information on the perception of vitality forms generated by a humanoid robot. In this study, two fMRI experiments were conducted in order to investigate whether and how the observation of actions generated by a humanoid robot (iCub) with low and fast velocities (Study 1) or replicating gentle and rude human forms (Study 2) may convey vitality forms eliciting the activation of the dorso-central insula. These studies showed that the observation of robotic actions, generated with low and high velocities, resulted in activation of the parieto-frontal circuit typically involved in the recognition and the execution of human actions but not of the insula (Study 1). Most interestingly, the observation of robotic actions, generated by replicating gentle and rude human vitality forms, produced a BOLD signal increase in the dorso-central insula (Study 2). In conclusion, these data highlight the selective role of dorso-central insula in the processing of vitality forms opening future perspectives on the perception and understanding of actions performed by humanoid robots.

Regulatory Functions of L-Carnitine, Acetyl, and Propionyl L-Carnitine in a PCOS Mouse Model: Focus on Antioxidant/Antiglycative Molecular Pathways in the Ovarian Microenvironment

Polycystic ovary syndrome (PCOS) is a complex metabolic disorder associated with female infertility. Based on energy and antioxidant regulatory functions of carnitines, we investigated whether acyl-L-carnitines improve PCOS phenotype in a mouse model induced by dehydroepiandrosterone (DHEA). CD1 mice received DHEA for 20 days along with two different carnitine formulations: one containing L-carnitine (LC) and acetyl-L-carnitine (ALC), and the other one containing also propionyl-L-carnitine (PLC). We evaluated estrous cyclicity, testosterone level, ovarian follicle health, ovulation rate and oocyte quality, collagen deposition, lipid droplets, and 17ß-HSD IV (17 beta-hydroxysteroid dehydrogenase type IV) expression. Moreover, we analyzed protein expression of SIRT1, SIRT3, SOD2 (superoxide dismutase 2), mitochondrial transcriptional factor A (mtTFA), RAGE (receptor for AGEs), GLO2 (glyoxalase 2) and ovarian accumulation of MG-AGEs (advanced glycation end-products formed by methylglyoxal). Both carnitine formulations ameliorated ovarian PCOS phenotype and positively modulated antioxidant molecular pathways in the ovarian microenvironment. Addition of PLC to LC-ALC formulation mitigated intraovarian MG-AGE accumulation and increased mtTFA expression. In conclusion, our study supports the hypothesis that oral administration of acyl-L-carnitines alleviates ovarian dysfunctions associated with this syndrome and that co-administration of PLC provides better activity. Molecular mechanisms underlying these effects include anti-oxidant/glycative activity and potentiation of mitochondria.

A transition clinic model for inflammatory bowel disease between two tertiary care centers: outcomes and predictive factors

OBJECTIVE

Few models of transition have been proposed for inflammatory bowel disease (IBD). The aim of the present study is to evaluate the feasibility of a transition model and the predictive factors for success/failure.

PATIENTS AND METHODS

Patients with low activity or remission IBD were enrolled. Proposed model: three meetings every four-six weeks: the first one in the pediatric center (Bambino Gesù Children's Hospital); the second one, in the adult center (Foundation Polyclinic University A. Gemelli), with pediatric gastroenterologists; the last one, in the adult center, with adult gastroenterologists only. Questionnaires included anxiety and depression clinical scale, self-efficacy, quality of life, visual-analogic scale (VAS). Transition was considered successful if the three steps were completed.

RESULTS

Twenty patients were enrolled (range 18-25 years; M/F: 12/8; Ulcerative Colitis/Crohn's Disease 10/10); eight accepted the transition program, four delayed the process and eight refused. Patients who completed transition generated higher scores on the resilience scale, better scores on well-being perception, and had lower anxiety scores. Patients who failed transition were mostly women. The perceived utility of the transition program was scored 7.3 on a VAS scale.

CONCLUSIONS

The proposed transition program seems to be feasible. Psychological scores may help in selecting patients and predicting outcomes.

Methylglyoxal-Dependent Glycative Stress and Deregulation of SIRT1 Functional Network in the Ovary of PCOS Mice

Advanced glycation end-products (AGEs) are involved in the pathogenesis and consequences of polycystic ovary syndrome (PCOS), a complex metabolic disorder associated with female infertility. The most powerful AGE precursor is methylglyoxal (MG), a byproduct of glycolysis, that is detoxified by the glyoxalase system. By using a PCOS mouse model induced by administration of dehydroepiandrosterone (DHEA), we investigated whether MG-dependent glycative stress contributes to ovarian PCOS phenotype and explored changes in the Sirtuin 1 (SIRT1) functional network regulating mitochondrial functions and cell survival. In addition to anovulation and reduced oocyte quality, DHEA ovaries revealed altered collagen deposition, increased vascularization, lipid droplets accumulation and altered steroidogenesis. Here we observed increased intraovarian MG-AGE levels in association with enhanced expression of receptor for AGEs (RAGEs) and deregulation of the glyoxalase system, hallmarks of glycative stress. Moreover, DHEA mice exhibited enhanced ovarian expression of SIRT1 along with increased protein levels of SIRT3 and superoxide dismutase 2 (SOD2), and decreased peroxisome proliferator-activated receptor gamma co-activator 1 alpha (PGC1α), mitochondrial transcriptional factor A (mtTFA) and translocase of outer mitochondrial membrane 20 (TOMM20). Finally, the presence of autophagy protein markers and increased AMP-activated protein kinase (AMPK) suggested the involvement of SIRT1/AMPK axis in autophagy activation. Overall, present findings demonstrate that MG-dependent glycative stress is involved in ovarian dysfunctions associated to PCOS and support the hypothesis of a SIRT1-dependent adaptive response.

Can a Robot Catch You Lying? A Machine Learning System to Detect Lies During Interactions

Deception is a complex social skill present in human interactions. Many social professions such as teachers, therapists and law enforcement officers leverage on deception detection techniques to support their work activities. Robots with the ability to autonomously detect deception could provide an important aid to human-human and human-robot interactions. The objective of this work is to demonstrate the possibility to develop a lie detection system that could be implemented on robots. To this goal, we focus on human and human robot interaction to understand if there is a difference in the behavior of the participants when lying to a robot or to a human. Participants were shown short movies of robberies and then interrogated by a human and by a humanoid robot "detectives." According to the instructions, subjects provided veridical responses to half of the question and false replies to the other half. Behavioral variables such as eye movements, time to respond and eloquence were measured during the task, while personality traits were assessed before experiment initiation. Participant's behavior showed strong similarities during the interaction with the human and the humanoid. Moreover, the behavioral features were used to train and test a lie detection algorithm. The results show that the selected behavioral variables are valid markers of deception both in human-human and in human-robot interactions and could be exploited to effectively enable robots to detect lies.