Cerebral hemodynamics monitoring during extracorporeal membrane oxygenation in piglets

Critically ill neonates are subjected to severe and abrupt hemodynamic imbalances that could cause cerebral damage (e.g., hemorrhage, ischemic events). In this population, the need for cerebral monitoring tools to identify dangerous hemodynamic variations in real-time is paramount. Near-infrared spectroscopy (NIRS) is largely exploited in neonatal intensive care units (NICU) to monitor critically ill patients' cerebral oxygenation. However, the most used NIRS devices exploit continuous wave NIRS (CW NIRS) technique, which is affected by motion artifacts and has low penetration depth compared to other more complex NIRS techniques. Moreover, CW-NIRS does not allow the investigation of tissue perfusion. Thus, in this ongoing study, we tested a hybrid device that combines time-domain NIRS (TD-NIRS) and diffuse correlation spectroscopy (DCS) for monitoring absolute cerebral total hemoglobin concentration (tHb), cerebral tissue oxygen saturation (StO2), and cerebral blood flow index (BFI) of piglets during induced hemodynamic variations. Cerebral hemodynamic variations were induced during extracorporeal membrane oxygenation (ECMO) procedure, simulating four common conditions affecting the cerebral hemodynamics of ill neonates: hypocapnia, hypercapnia, hypotension, and hypertension. We measured 4 piglets, and the preliminary results shown in this study are promising, obtaining hemodynamic variations in accordance with previous findings, and empowering the possibility to exploit hybrid TD-NIRS and DCS devices to assess cerebral health of ill neonates

β3 Adrenoceptor Agonism Prevents Hyperoxia-Induced Colonic Alterations

Oxygen level is a key regulator of organogenesis and its modification in postnatal life alters the maturation process of organs, including the intestine, which do not completely develop in utero. The β3-adrenoreceptor (β3-AR) is expressed in the colon and has an oxygen-dependent regulatory mechanism. This study shows the effects of the β3-AR agonist BRL37344 in a neonatal model of hyperoxia-driven colonic injury. For the first 14 days after birth, Sprague–Dawley rat pups were exposed to ambient oxygen levels (21%) or hyperoxia (85%) and treated daily with BRL37344 at 1, 3, 6 mg/kg or untreated. At the end of day 14, proximal colon samples were collected for analysis. Hyperoxia deeply influences the proximal colon development by reducing β3-AR-expressing cells (27%), colonic length (26%) and mucin production (47%), and altering the neuronal chemical coding in the myenteric plexus without changes in the neuron number. The administration of BRL37344 at 3 mg/kg, but not at 1 mg/kg, significantly prevented these alterations. Conversely, it was ineffective in preventing hyperoxia-induced body weight loss. BRL37344 at 6 mg/kg was toxic. These findings pave the way for β3-AR pharmacological targeting as a therapeutic option for diseases caused by hyperoxia-impaired development, typical prematurity disorders

Description of the Exposure of the Most-Followed Spanish Instamoms’ Children to Social Media

There is evidence of the risk of overexposure of children on social networks by parents working as influencers. A cross-sectional study of the profiles of the sixteen most-followed Instamoms in Spain was carried out. An analysis of these profiles was performed over a full month (April 2022), three times a week, to describe the representation of influencers’ children in the posts shared by them, as well as their role in the Instamoms’ marketing. A total of 192 evaluations of the profiles were performed in the study period. The average number of children exposed by an Instamom was three, generally preschoolers and schoolchildren. The children appear in a context of the family home and accompanied by their mother. The type of advertising that accompanies the appearance of underage children is usually women or children’s clothing, but also food products, leisure, etc. Appearance of children in the posts had a statistically significant influence on followers measured by the number of likes. Results provided the identification of two Instamom clusters with differentiated behaviors in relation to appearance of children in posts. It is important to involve Social Pediatrics in the protection of the privacy and interests of children given the increase in sharenting. The authors believe that there are concerns about their explicit consent to public exposure from early childhood and about the medium and long-term effect that this may have on their future well-being.10 página

Social network analysis: the use of graph distances to compare artificial and criminal networks

Aim: Italian criminal groups become more and more dangerous spreading their activities into new sectors. A criminal group is made up of networks of hundreds of family gangs which extended their influence across the world, raking in billions from drug trafficking, extortion and money laundering. We focus in particular on the analysis of the social structure of two Sicilian crime families and we used a Social Network Analysis approach to study the social phenomena. Starting from a real criminal network extracted from meetings emerging from the police physical surveillance during 2000s, we here aim to create artificial models that present similar properties. Methods: We use specific tools of social network analysis and graph theory such as network models (i.e., random, small-world and scale-free) and graph distances to quantify the similarity between an artificial network and a real one. To the best of our knowledge, spectral graph distances and the DeltaCon similarity have never been applied to criminal networks. Results: Our experiments identify the Barabási-Albert model as the one which better represents a criminal network. For this reason, we could expect that new members of a criminal organization will be more likely to establish connections with high degree nodes rather than low degree nodes. Conclusion: Artificial but realistic models can represent a useful tool for Law Enforcement Agencies to simulate and study the structure, evolution and faults of criminal networks.N/

Current pain management practices for preterm infants with necrotizing enterocolitis:a European survey

Background: Necrotizing enterocolitis (NEC) is a highly painful intestinal complication in preterm infants that requires adequate pain management to prevent short- and long-term effects of neonatal pain. There is a lack of international guidelines for pain management in NEC patients. Therefore, this study aims to describe current pain management for NEC patients in European neonatal intensive care units (NICUs). Methods: An online survey was designed and conducted to assess current practices in pain management for NEC patients in European NICUs. The survey was distributed via neonatal societies, digital platforms, and professional contacts. Results: Out of the 259 responding unique European NICUs from 36 countries, 61% had a standard protocol for analgesic therapy, 73% assessed pain during NEC, and 92% treated NEC patients with intravenous analgosedatives. There was strong heterogeneity in the used pain scales and initial analgesic therapy, which mainly included acetaminophen (70%), fentanyl (56%), and/or morphine (49%). A third of NICU representatives considered their pain assessment adequate, and half considered their analgesic therapy adequate for NEC patients. Conclusions: Various pain scales and analgesics are used to treat NEC patients in European NICUs. Our results provide the first step towards an international guideline to improve pain management for NEC patients. Impact: This study provides an overview of current pain management practices for infants with necrotizing enterocolitis (NEC) in European neonatal intensive care units.Choice of pain assessment tools, analgosedatives, and dosages vary considerably among NICUs and countries.A third of NICU representatives were satisfied with their current pain assessment practices and half of NICU representatives with their analgesic therapy practices in NEC patients in their NICU.The results of this survey may provide a first step towards developing a European pain management consensus guideline for patients with NEC.</p

Oxidative Stress and Neonatal Respiratory Extracorporeal Membrane Oxygenation

Oxidative stress is a frequent condition in critically ill patients, especially if exposed to extracorporeal circulation, and it is associated with worse outcomes and increased mortality. The inflammation triggered by the contact of blood with a non-endogenous surface, the use of high volumes of packed red blood cells and platelets transfusion, the risk of hyperoxia and the impairment of antioxidation systems contribute to the increase of reactive oxygen species and the imbalance of the redox system. This is responsible for the increased production of superoxide anion, hydrogen peroxide, hydroxyl radicals, and peroxynitrite resulting in increased lipid peroxidation, protein oxidation, and DNA damage. The understanding of the pathophysiologic mechanisms leading to redox imbalance would pave the way for the future development of preventive approaches. This review provides an overview of the clinical impact of the oxidative stress during neonatal extracorporeal support and concludes with a brief perspective on the current antioxidant strategies, with the aim to focus on the potential oxidative stress-mediated cell damage that has been implicated in both short and long-term outcomes

Criminal networks analysis in missing data scenarios through graph distances

Data collected in criminal investigations may suffer from issues like: (i) incompleteness, due to the covert nature of criminal organizations; (ii) incorrectness, caused by either unintentional data collection errors or intentional deception by criminals; (iii) inconsistency, when the same information is collected into law enforcement databases multiple times, or in different formats. In this paper we analyze nine real criminal networks of different nature (i.e., Mafia networks, criminal street gangs and terrorist organizations) in order to quantify the impact of incomplete data, and to determine which network type is most affected by it. The networks are firstly pruned using two specific methods: (i) random edge removal, simulating the scenario in which the Law Enforcement Agencies fail to intercept some calls, or to spot sporadic meetings among suspects; (ii) node removal, modeling the situation in which some suspects cannot be intercepted or investigated. Finally we compute spectral distances (i.e., Adjacency, Laplacian and normalized Laplacian Spectral Distances) and matrix distances (i.e., Root Euclidean Distance) between the complete and pruned networks, which we compare using statistical analysis. Our investigation identifies two main features: first, the overall understanding of the criminal networks remains high even with incomplete data on criminal interactions (i.e., when 10% of edges are removed); second, removing even a small fraction of suspects not investigated (i.e., 2% of nodes are removed) may lead to significant misinterpretation of the overall network.Libera Università di Bolzan

Disrupting resilient criminal networks through data analysis: The case of Sicilian Mafia

Compared to other types of social networks, criminal networks present particularly hard challenges, due to their strong resilience to disruption, which poses severe hurdles to Law-Enforcement Agencies (LEAs). Herein, we borrow methods and tools from Social Network Analysis (SNA) to (i) unveil the structure and organization of Sicilian Mafia gangs, based on two real-world datasets, and (ii) gain insights as to how to efficiently reduce the Largest Connected Component (LCC) of two networks derived from them. Mafia networks have peculiar features in terms of the links distribution and strength, which makes them very different from other social networks, and extremely robust to exogenous perturbations. Analysts also face difficulties in collecting reliable datasets that accurately describe the gangs’ internal structure and their relationships with the external world, which is why earlier studies are largely qualitative, elusive and incomplete. An added value of our work is the generation of two real-world datasets, based on raw data extracted from juridical acts, relating to a Mafia organization that operated in Sicily during the first decade of 2000s. We created two different networks, capturing phone calls and physical meetings, respectively. Our analysis simulated different intervention procedures: (i) arresting one criminal at a time (sequential node removal); and (ii) police raids (node block removal). In both the sequential, and the node block removal intervention procedures, the Betweenness centrality was the most effective strategy in prioritizing the nodes to be removed. For instance, when targeting the top 5% nodes with the largest Betweenness centrality, our simulations suggest a reduction of up to 70% in the size of the LCC. We also identified that, due the peculiar type of interactions in criminal networks (namely, the distribution of the interactions’ frequency), no significant differences exist between weighted and unweighted network analysis. Our work has significant practical applications for perturbing the operations of criminal and terrorist networks