Mean-Field Selective Optimal Control via Transient Leadership

A mean-field selective optimal control problem of multipopulation dynamics via transient leadership is considered. The agents in the system are described by their spatial position and their probability of belonging to a certain population. The dynamics in the control problem is characterized by the presence of an activation function which tunes the control on each agent according to the membership to a population, which, in turn, evolves according to a Markov-type jump process. In this way, a hypothetical policy maker can select a restricted pool of agents to act upon based, for instance, on their time-dependent influence on the rest of the population. A finite-particle control problem is studied and its mean-field limit is identified via Γ -convergence, ensuring convergence of optimal controls. The dynamics of the mean-field optimal control is governed by a continuity-type equation without diffusion. Specific applications in the context of opinion dynamics are discussed with some numerical experiments.

Biological Frailty Index in centenarians

This study measured the subclinical frailty of centenarians by looking at the accumulation of their biological abnormalities. For this aim, a biological Frailty Index (FI) was computed in centenarians living in Northern Italy. The median value of the biological FI was 0.33 (interquartile range, IQR 0.28–0.41). The biological FI did not significantly differ between women (0.34, IQR 0.31–0.39) and men (0.32, IQR 0.26–0.43). The biological FI seems to have a narrower distribution compared to clinical FI we previously computed in the same cohort. In conclusion, our study suggests that centenarians benefit from exceptional biological reserves that might be underestimated by clinical appearances.

Measuring close proximity interactions in summer camps during the COVID-19 pandemic

Policy makers have implemented multiple non-pharmaceutical strategies to mitigate the COVID-19 worldwide crisis. Interventions had the aim of reducing close proximity interactions, which drive the spread of the disease. A deeper knowledge of human physical interactions has revealed necessary, especially in all settings involving children, whose education and gathering activities should be preserved. Despite their relevance, almost no data are available on close proximity contacts among children in schools or other educational settings during the pandemic. Contact data are usually gathered via Bluetooth, which nonetheless offers a low temporal and spatial resolution. Recently, ultra-wideband (UWB) radios emerged as a more accurate alternative that nonetheless exhibits a significantly higher energy consumption, limiting in-field studies. In this paper, we leverage a novel approach, embodied by the Janus system that combines these radios by exploiting their complementary benefits. The very accurate proximity data gathered in-field by Janus, once augmented with several metadata, unlocks unprecedented levels of information, enabling the development of novel multi-level risk analyses. By means of this technology, we have collected real contact data of children and educators in three summer camps during summer 2020 in the province of Trento, Italy. The wide variety of performed daily activities induced multiple individual behaviors, allowing a rich investigation of social environments from the contagion risk perspective. We consider risk based on duration and proximity of contacts and classify interactions according to different risk levels. We can then evaluate the summer camps' organization, observe the effect of partition in small groups, or social bubbles, and identify the organized activities that mitigate the riskier behaviors. Overall, we offer an insight into the educator-child and child-child social interactions during the pandemic, thus providing a valuable tool for schools, summer camps, and policy makers to (re)structure educational activities safely.

A cyber warfare perspective on risks related to health IoT devices and contact tracing

The wide use of IT resources to assess and manage the recent COVID-19 pandemic allows to increase the effectiveness of the countermeasures and the pervasiveness of monitoring and prevention. Unfortunately, the literature reports that IoT devices, a widely adopted technology for these applications, are characterized by security vulnerabilities that are difficult to manage at the state level. Comparable problems exist for related technologies that leverage smartphones, such as contact tracing applications, and non-medical health monitoring devices. In analogous situations, these vulnerabilities may be exploited in the cyber domain to overload the crisis management systems with false alarms and to interfere with the interests of target countries, with consequences on their economy and their political equilibria. In this paper we analyze the potential threat to an example subsystem to show how these influences may impact it and evaluate a possible consequence.

The creation of phenomena in interactive biorobotics

In so-called interactive biorobotics, robotic models of living systems interact with animals in controlled experimental settings. By observing how the focal animal reacts to the stimuli delivered by the robot, one tests hypotheses concerning the determinants of animal behaviour in social contexts. Building on previous methodological reconstructions of interactive biorobotics, this article reflects on the claim, made by several authors in the field, that this strategy may enable one to explain social phenomena in animals. The answer offered here will be negative: interactive biorobotics does not contribute to the explanation of social phenomena. However, it may greatly contribute to the study of animal behaviour by creating social phenomena in the sense discussed by Ian Hacking, i.e. by precisely defining new phenomena to be explained. It will be also suggested that interactive biorobotics can be combined with more classical robot-based approaches to the study of living systems, leading to a so-called simulation-interactive strategy for the mechanistic explanation of social behaviour in animals.

Minimal AR: visual asset optimization for the authoring of augmented reality work instructions in manufacturing

This work investigates the possibility of using a novel "minimal AR" authoring approach to optimize the visual assets used in augmented reality (AR) interfaces to convey work instructions in manufacturing. In the literature, there are no widely supported guidelines for the optimal choice of visual assets (e.g., CAD models, drawings, and videos). Therefore, to avoid the risk of having AR technical documentation based only on the author's preference, our work proposes a novel authoring approach that enforces the minimal amount of information to accomplish a task. Minimal AR was tested through a simulated AR LEGO-based assembly task. The performance (completion time, mental workload, errors) of 40 users was evaluated with 4 combinations of visual assets in 4 tasks with an increasing amount of information needed. The main result is that visual assets with an excess of information do not significantly increase performance. Therefore, the location of a specified object should be "minimally" authored by an auxiliary model (e.g., a circle and an arrow). For identifying an object within a couple, color coding is preferred to using additional visual assets. If more than two objects must be identified, a drawing visual asset is also needed. Only when the orientation of a selected object must be conveyed, animated product models are required. These insights could be helpful for an optimal design of AR work instructions in a wide range of industrial fields.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s00170-021-08449-6.

VEGF-A/VEGFR-1 signalling and chemotherapy-induced neuropathic pain: therapeutic potential of a novel anti-VEGFR-1 monoclonal antibody

BACKGROUND

Neuropathic pain is a clinically relevant adverse effect of several anticancer drugs that markedly impairs patients' quality of life and frequently leads to dose reduction or therapy discontinuation. The poor knowledge about the mechanisms involved in neuropathy development and pain chronicization, and the lack of effective therapies, make treatment of chemotherapy-induced neuropathic pain an unmet medical need. In this context, the vascular endothelial growth factor A (VEGF-A) has emerged as a candidate neuropathy hallmark and its decrease has been related to pain relief. In the present study, we have investigated the role of VEGF-A and its receptors, VEGFR-1 and VEGFR-2, in pain signalling and in chemotherapy-induced neuropathy establishment as well as the therapeutic potential of receptor blockade in the management of pain.

METHODS

Behavioural and electrophysiological analyses were performed in an in vivo murine model, by using selective receptor agonists, blocking monoclonal antibodies or siRNA-mediated silencing of VEGF-A and VEGFRs. Expression of VEGF-A and VEGFR-1 in astrocytes and neurons was detected by immunofluorescence staining and confocal microscopy analysis.

RESULTS

In mice, the intrathecal infusion of VEGF-A (VEGF165 isoforms) induced a dose-dependent noxious hypersensitivity and this effect was mediated by VEGFR-1. Consistently, electrophysiological studies indicated that VEGF-A strongly stimulated the spinal nociceptive neurons activity through VEGFR-1. In the dorsal horn of the spinal cord of animals affected by oxaliplatin-induced neuropathy, VEGF-A expression was increased in astrocytes while VEGFR-1 was mainly detected in neurons, suggesting a VEGF-A/VEGFR-1-mediated astrocyte-neuron cross-talk in neuropathic pain pathophysiology. Accordingly, the selective knockdown of astrocytic VEGF-A by intraspinal injection of shRNAmir blocked the development of oxaliplatin-induced neuropathic hyperalgesia and allodynia. Interestingly, both intrathecal and systemic administration of the novel anti-VEGFR-1 monoclonal antibody D16F7, endowed with anti-angiogenic and antitumor properties, reverted oxaliplatin-induced neuropathic pain. Besides, D16F7 effectively relieved hypersensitivity induced by other neurotoxic chemotherapeutic agents, such as paclitaxel and vincristine.

CONCLUSIONS

These data strongly support the role of the VEGF-A/VEGFR-1 system in mediating chemotherapy-induced neuropathic pain at the central nervous system level. Thus, treatment with the anti-VEGFR-1 mAb D16F7, besides exerting antitumor activity, might result in the additional advantage of attenuating neuropathic pain when combined with neurotoxic anticancer agents.

Adherence to Lipid-Lowering Treatment by Single-Pill Combination of Statin and Ezetimibe

INTRODUCTION

Although several studies have shown that a simplified cardiovascular drug treatment leads to better treatment adherence, limited and conflicting findings have been reported on the separate or single-pill combination of the now recommended association between a statin and ezetimibe. We addressed this issue in a large cohort of patients newly treated with statins to whom ezetimibe was additionally administered, either separately or as a single-pill combination.

METHODS

A total of 256,012 patients (age 40-80 years) from the Lombardy Region (Italy) newly treated with statins during 2011-2013 were followed until 2018 to identify those to whom ezetimibe was added. The 2881 and 5351 patients who started a two-pill or a single-pill combination, respectively, of statin and ezetimibe were identified and matched for propensity score. Adherence to drug therapy at 1 year was measured as the ratio between the number of days in which the drug was available and the days of follow-up (the proportion of days covered; PDC). Patients who had a PDC > 75% or < 25% were, respectively, defined as highly and poorly adherent to drug therapy. Analysis was extended to the association between adherence and the risk of fatal/non-fatal cardiovascular events.

RESULTS

Compared to those prescribed a two-pill combination, those prescribed a single-pill combination had an 87% (75-99%) greater odds of being highly adherent and a 79% (72-84%) lower odds of being poorly adherent to treatment. These advantages were manifest in all strata of age, sex, and clinical profile. The risk of cardiovascular outcomes decreased by 55% in patients with high adherence compared to those with low adherence.

CONCLUSION

Patients who were prescribed a single-pill combination of statin/ezetimibe more frequently exhibit a good adherence and less frequently bad adherence to treatment than those prescribed a two-pill combination of these drugs.

N-Acylethanolamine Acid Amidase Inhibition Potentiates Morphine Analgesia and Delays the Development of Tolerance

Opioids are essential drugs for pain management, although long-term use is accompanied by tolerance, necessitating dose escalation, and dependence. Pharmacological treatments that enhance opioid analgesic effects and/or attenuate the development of tolerance (with a desirable opioid-sparing effect in treating pain) are actively sought. Among them, N-palmitoylethanolamide (PEA), an endogenous lipid neuromodulator with anti-inflammatory and neuroprotective properties, was shown to exert anti-hyperalgesic effects and to delay the emergence of morphine tolerance. A selective augmentation in endogenous PEA levels can be achieved by inhibiting N-acylethanolamine acid amidase (NAAA), one of its primary hydrolyzing enzymes. This study aimed to test the hypothesis that NAAA inhibition, with the novel brain permeable NAAA inhibitor AM11095, modulates morphine's antinociceptive effects and attenuates the development of morphine tolerance in rats. We tested this hypothesis by measuring the pain threshold to noxious mechanical stimuli and, as a neural correlate, we conducted in vivo electrophysiological recordings from pain-sensitive locus coeruleus (LC) noradrenergic neurons in anesthetized rats. AM11095 dose-dependently (3-30 mg/kg) enhanced the antinociceptive effects of morphine and delayed the development of tolerance to chronic morphine in behaving rats. Consistently, AM11095 enhanced morphine-induced attenuation of the response of LC neurons to foot-shocks and prevented the attenuation of morphine effects following chronic treatment. Behavioral and electrophysiological effects of AM11095 on chronic morphine were paralleled by a decrease in glial activation in the spinal cord, an index of opioid-induced neuroinflammation. NAAA inhibition might represent a potential novel therapeutic approach to increase the analgesic effects of opioids and delay the development of tolerance.

An Investigation into the Temporal Reproducibility of Tryptophan Metabolite Networks Among Healthy Adolescents

Tryptophan and its bioactive metabolites are associated with health conditions such as systemic inflammation, cardiometabolic diseases, and neurodegenerative disorders. There are dynamic interactions among metabolites of tryptophan. The interactions between metabolites, particularly those that are strong and temporally reproducible could be of pathophysiological relevance. Using a targeted metabolomics approach, the concentration levels of tryptophan and 18 of its metabolites across multiple pathways was quantified in 24-hours urine samples at 2 time-points, age 17 years (baseline) and 18 years (follow-up) from 132 (52% female) apparently healthy adolescent participants of the DOrtmund Nutritional and Anthropometric Longitudinally Designed (DONALD) Study. In sex-specific analyses, we applied 2 network approaches, the Gaussian graphical model and Bayesian network to (1) explore the network structure for both time-points, (2) retrieve strongly related metabolites, and (3) determine whether the strongly related metabolites were temporally reproducible. Independent of selected covariates, the 2 network approaches revealed 5 associations that were strong and temporally reproducible. These were novel relationships, between kynurenic acid and indole-3-acetic acid in females and between kynurenic acid and xanthurenic acid in males, as well as known relationships between kynurenine and 3-hydroxykynurenine, and between 3-hydroxykynurenine and 3-hydroxyanthranilic acid in females and between tryptophan and kynurenine in males. Overall, this epidemiological study using network-based approaches shed new light into tryptophan metabolism, particularly the interaction of host and microbial metabolites. The 5 observed relationships suggested the existence of a temporally stable pattern of tryptophan and 6 metabolites in healthy adolescent, which could be further investigated in search of fingerprints of specific physiological states. The metabolites in these relationships may represent a multi-biomarker panel that could be informative for health outcomes.

Continuity of the temperature in a multi-phase transition problem

Locally bounded, local weak solutions to a doubly nonlinear parabolic equation, which models the multi-phase transition of a material, is shown to be locally continuous. Moreover, an explicit modulus of continuity is given. The effect of the p-Laplacian type diffusion is also considered.

Detection of Insulin Pump Malfunctioning to Improve Safety in Artificial Pancreas Using Unsupervised Algorithms

BACKGROUND

Recent development of automated closed-loop (CL) insulin delivery systems, the so-called artificial pancreas (AP), improved the quality of type 1 diabetes (T1D) therapy. As new technologies emerge, patients put increasing trust in their therapeutic devices; therefore, it becomes increasingly important to detect malfunctioning affecting such devices. In this work, we explore a new paradigm to detect insulin pump faults (IPFs) that use unsupervised anomaly detection.

METHODS

We generated CL data corrupted with IPFs using the latest version of the T1D Padova/UVA simulator. From the data, we extracted several features capable to describe the patient dynamics and making more apparent suspicious data portions. Then, a feature selection is performed to determine the optimal feature set. Finally, the performance of several popular unsupervised anomaly detection algorithms is analyzed and compared on the identified optimal feature set.

RESULTS

Using the identified optimal configuration, the best performance is obtained by the Histogram-Based Outlier Score (HBOS) algorithm, which detected 87% of the IPF with only 0.08 false positives per day on average. Isolation forest is the best algorithm that offers more conservative performances, detection of 85% of the faults but only 0.06 false positives per day on average.

CONCLUSION

Unsupervised anomaly detection algorithms can be used effectively to detect IPFs and improve the safety of the AP. Future studies will be dedicated to test the presented method inside dedicated clinical trials.

Influence of the pH control strategy and reactor volume on batch fermentative hydrogen production from the organic fraction of municipal solid waste

Three different experimental sets of runs involving batch fermentation assays were performed to evaluate the influence of the experimental conditions on biological hydrogen production from the source-separated organic fraction of municipal solid waste collected through a door-to-door system. The fermentation process was operated with and without automatic pH control, at a pH of 5.5 and 6.5, food-to-microorganism ratios of 1/3 and 1/1 (wet weight basis) and with different working volumes (0.5 and 3 L). The experimental results showed that the pH control strategy and the reactor volume did not affect the final hydrogen production yield but played an important role in determining the time evolution of the process. Indeed, although the different experimental conditions tested yielded comparable hydrogen productions (with maximum average values ranging from 68.5 to 88.5 NLH₂ (kgTVS_OF)^-1), the automatic pH control strategy improved the process from the kinetic viewpoint resulting in a t₉₅ reduction from an average of 34.9 h without automatic pH control to an average of 19.5 h.