Serum from COVID-19 patients promotes endothelial cell dysfunction through protease-activated receptor 2

Background: Endothelial dysfunction plays a central role in the pathophysiology of COVID-19 and is closely linked to the severity and mortality of the disease. The inflammatory response to SARS-CoV-2 infection can alter the capacity of the endothelium to regulate vascular tone, immune responses, and the balance between anti-thrombotic and pro-thrombotic properties. However, the specific endothelial pathways altered during COVID-19 still need to be fully understood. Objective: In this study, we sought to identify molecular changes in endothelial cells induced by circulating factors characteristic of COVID-19. Methods and results: To this aim, we cultured endothelial cells with sera from patients with COVID-19 or non-COVID-19 pneumonia. Through transcriptomic analysis, we were able to identify a distinctive endothelial phenotype that is induced by sera from COVID-19 patients. We confirmed and expanded this observation in vitro by showing that COVID-19 serum alters functional properties of endothelial cells leading to increased apoptosis, loss of barrier integrity, and hypercoagulability. Furthermore, we demonstrated that these endothelial dysfunctions are mediated by protease-activated receptor 2 (PAR-2), as predicted by transcriptome network analysis validated by in vitro functional assays. Conclusion: Our findings provide the rationale for further studies to evaluate whether targeting PAR-2 may be a clinically effective strategy to counteract endothelial dysfunction in COVID-19

A thorough analysis of the occurrence, removal and environmental risks of organic micropollutants in a full-scale hybrid membrane bioreactor fed by hospital wastewater

The recent draft of the Urban Wastewater Treatment Directive pays attention to contaminants of emerging concern including organic micropollutants (OMPs) and requires the removal of some of them at large urban wastewater treatment plants (WWTPs) calling for their upgrading. Many investigations to date have reported the occurrence of a vast group of OMPs in the raw influent and many technologies have been tested for their removal at a lab- or pilot-scale. Moreover, hospital wastewater (HWW) may contain specific OMPs at a high concentration and therefore its treatment deserves attention. In this study, a 1-year investigation was carried out at a full-scale membrane bioreactor (MBR) treating mainly HWW. To promote the removal of OMPs, powdered activated carbon (PAC) was added to the bioreactor at 0.1 g/L and 0.2 g/L which resulted in the MBR operating as a hybrid MBR. Its performance was tested for 232 target and 90 non-target OMPs, analysed by UHPLC-QTOF-MS using a direct injection method. The wastewater arriving at the WWTP was characterized and the performance of both the MBR and hybrid MBR was assessed for: key OMPs selected on the basis of their frequency, occurrence, persistence to removal, bioaccumulation and toxicity; OMP classes; and the whole list of OMPs. Finally, an environmental risk assessment of the OMP residues was conducted by means of the risk quotient approach. The results indicate that PAC addition increased the removal of most of the key OMPs (e.g., sulfamethoxazole, diclofenac, lidocaine) and OMP classes (e.g., antibiotics, psychiatric drugs and stimulants) with the highest loads in the WWTP influent. The hybrid MBR also reduced the risk in the receiving water as the PAC dosage increased mainly for spiramycin, lorazepam, oleandomycin. Finally, uncertainties and issues related to the investigation being carried out at full-scale under real conditions are discussed in depth

Carbonate factory response through the MECO (Middle Eocene Climate Optimum) event: Insight from the Apulia Carbonate Platform, Gargano Promontory, Italy

During the Eocene, shallow-water carbonate systems were significantly impacted by climate fluctuations and hyperthermal events. Following the peak temperatures of the Early Eocene Climatic Optimum (EECO), a general cooling trend began, with short-lived (⁓200 kyr) warming events occurring alongside it. In the early Bartonian (around 40.1 Ma), a warming event known as the Middle Eocene Climatic Optimum (MECO) occurred, lasting approximately 500,000 years. In this scenario, the types and calcification rates of marine organisms such as corals and larger benthic foraminifera (LBF) were influenced by global CO2 and oceanographic changes, which had a major effect on photic carbonate factories. To better understand the effects of these factors on carbonate factories, a detailed study of shallow-water facies types, distributions, and evolution was conducted. The Middle Eocene Monte Saraceno sequence, located on the eastern margin of the Apulia Carbonate Platform (Gargano Promontory, southern Italy), was selected as a case study to investigate the relationships between carbonate factory types and climatic changes around theMECO event. This study identified twodistinct intervalswith different modes of carbonate production, separated by a sharp boundary. The lower interval consists of clinostratified, thick beds of rudstone to floatstone, mostly made up of various large Nummulites tests, indicating an early Bartonian age (Shallow Benthic Zone 17). Instead, the upper interval consists of coral floatstone to rudstone with a packstone matrix, rich in branching corals in association with gastropods, bivalves, and rare small larger benthic foraminifera. The appearance of Heterostegina sp. and Glomalveolina ungaroi in this interval indicates a late Bartonian age (Shallow Benthic Zone 18). By integrating biostratigraphic and stable-isotope data, the lower interval, with abundant Nummulites, was linked to the MECO event, duringwhich higher sea-surface temperatures seem to enhance larger benthic foraminifera proliferation, as already occurred in the Early Eocene. However, in the late Bartonian, the sharp transition to a coral-dominated carbonate factory,with rare larger benthic foraminifera showing smaller sizes, could be attributed to a drop in temperature that created the conditions more favourable to corals. Overall, this study provides compelling evidence of how environmental changes can affect marine carbonate production, also highlighting the importance of investigating these relationships, to better understand climate change in the past, present and near future

Intraspecific variation in invertebrate cognition: a review

A well-established field of research in vertebrates focuses on the variability of cognitive abilities within species. From mammals to fish, numerous studies have revealed remarkable differences in the cognitive phenotype among individuals, particularly in terms of sex or personality. However, many aspects of the mechanisms, genetics, and selective pressures that underlie individual cognitive variation remain unclear. Surprisingly, intraspecific variability in cognition has received much less attention in invertebrates, despite the increasing evidence of remarkable cognitive abilities in this group and the insights that could be gained from examining simultaneously two distinct taxa, namely vertebrates and invertebrates. In this review, we provide evidence that certain invertebrate species exhibit all the key features of cognitive variation observed in vertebrates, including differences related to sex and personality. In many cases, invertebrate studies have provided insights into the genetic basis, evolvability and response to selection of cognitive variability. Moreover, we highlight evidence for caste differences in eusocial insects, which are linked to task specialisation within the colony. This makes insect eusociality a valuable system for understanding how selection influences cognitive variation. We propose that cognitive variation in invertebrates may be more widespread than currently thought, and that selection may operate in a similar manner on two distantly related cognitive systems (vertebrates and invertebrates). Finally, we suggest that invertebrates hold the potential to serve both as alternative and complementary models to vertebrates, contributing to a deeper understanding of cognitive evolution

Chaos Engineering for Resilience Assessment of Digital Twins

Within the Industry 4.0 vision, Digital Twins (DTs) have gained great attention as a promising approach to improve remote monitoring and control by means of virtual representations of physical objects. However, while DTs are becoming more and more sophisticated and even adopted for mission-critical applications, their resilience assessment has not received the required consideration yet. This paper originally proposes Chaos Engineering to assess and improve the resilience of DTs by testing multiple aspects of industrial environments in a coordinated, automated, and replicable manner. First, the paper discusses why and how Chaos Engineering is promising to improve the resilience of DTs. Then, it identifies and introduces a set of Chaos Engineering profiles specifically designed to take into account the many aspects an industrial environment is composed of. Finally, it shows the feasibility of assessing the resilience of a proof-of-concept DT through a testbed based on widely-adopted, open-source tools

Methodology to Monitor Early Warnings Before Gas Turbine Trip

The current energy scenario requires that gas turbines (GTs) operate at their maximum efficiency and highest reliability. Trip is one of the most disrupting events that reduces GT availability and increases maintenance costs. To tackle the challenge of GT trip prediction, this paper presents a methodology that has the goal of monitoring the early warnings raised during GT operation and trigger an alert to avoid trip occurrence. The methodology makes use of an auto-encoder (prediction model) and a three-stage criterion (detection procedure). The auto-encoder is first trained to reconstruct safe operation data and subsequently tested on new data collected before trip occurrence. The trip detection criterion checks whether the individually tested data points should be classified as normal or anomalous (first stage), provides a warning if the anomaly score over a given time frame exceeds a threshold (second stage), and, finally, combines consecutive warnings to trigger a trip alert in advance (third stage). The methodology is applied to a real-world case study composed of a collection of trips, of which the causes may be different, gathered from various GTs in operation during several years. Historical observations of gas path measurements taken during three days of GT operation before trip occurrence are employed for the analysis. Once optimally tuned, the methodology provides a trip alert with a reliability equal to 75%at least 10 h in advance before trip occurrence

Machine learning from real data: A mental health registry case study

Imbalanced datasets can impair the learning performance of many Machine Learning techniques. Nevertheless, many real-world datasets, especially in the healthcare field, are inherently imbalanced. For instance, in the medical domain, the classes representing a specific disease are typically the minority of the total cases. This challenge justifies the substantial research effort spent in the past decades to tackle data imbalance at the data and algorithm levels. In this paper, we describe the strategies we used to deal with an imbalanced classification task on data extracted from a database generated from the Electronic Health Records of the Mental Health Service of the Ferrara Province, Italy. In particular, we applied balancing techniques to the original data, such as random undersampling and oversampling, and Synthetic Minority Oversampling Technique for Nominal and Continuous (SMOTE-NC). In order to assess the effectiveness of the balancing techniques on the classification task at hand, we applied different Machine Learning algorithms. We employed cost-sensitive learning as well and compared its results with those of the balancing methods. Furthermore, a feature selection analysis was conducted to investigate the relevance of each feature. Results show that balancing can help find the best setting to accomplish classification tasks. Since real-world imbalanced datasets are increasingly becoming the core of scientific research, further studies are needed to improve already existing techniqu

Respiratory Syncytial Virus Prefusion F Protein Vaccine Is Efficacious in Older Adults With Underlying Medical Conditions

Background: Older adults with chronic cardiorespiratory or endocrine/metabolic conditions are at increased risk of respiratory syncytial virus (RSV)-related acute respiratory illness (RSV-ARI) and severe respiratory disease. In an ongoing, randomized, placebo-controlled, multicountry, phase 3 trial in ≥60-year-old participants, an AS01E-adjuvanted RSV prefusion F protein-based vaccine (RSVPreF3 OA) was efficacious against RSV-related lower respiratory tract disease (RSV-LRTD), severe RSV-LRTD, and RSV-ARI. We evaluated efficacy and immunogenicity among participants with coexisting cardiorespiratory or endocrine/metabolic conditions that increase the risk of severe RSV disease ("conditions of interest"). Methods: Medically stable ≥60-year-old participants received 1 dose of RSVPreF3 OA or placebo. Efficacy against first RSV-LRTD and RSV-ARI episodes was assessed in subgroups with/without coexisting cardiorespiratory or endocrine/metabolic conditions of interest. Immunogenicity was analyzed post hoc in these subgroups. Results: In total, 12 467 participants received RSVPreF3 OA and 12 499 received placebo. Of these, 39.6% (RSVPreF3 OA) and 38.9% (placebo) had ≥1 coexisting condition of interest. The median efficacy follow-up was 6.7 months. Efficacy against RSV-LRTD was high in participants with ≥1 condition of interest (94.6%), ≥1 cardiorespiratory (92.1%), ≥1 endocrine/metabolic (100%), and ≥2 conditions of interest (92.0%). Efficacy against RSV-ARI was 81.0% in participants with ≥1 condition of interest (88.1% for cardiorespiratory, 79.4% for endocrine/metabolic conditions) and 88.0% in participants with ≥2 conditions of interest. Postvaccination neutralizing titers were at least as high in participants with ≥1 condition of interest as in those without. Conclusions: RSVPreF3 OA was efficacious against RSV-LRTD and RSV-ARI in older adults with coexisting medical conditions associated with an increased risk of severe RSV disease

L’inafferrabile fisionomia del Cyberlaundering

SOMMARIO 1. Il Cyberlaundering nel contesto digitale. – 2. Dalle prime forme di sfruttamento delle nuove tecnologie a fini di riciclaggio all’avvento delle valute virtuali. – 3. Le criptomonete: una nuova possibile declinazione dell’oggetto materiale del riciclaggio? – 4. I punti di forza (nella prospettiva dell’autore del reato) della dimensione digitale del riciclaggio. – 5. I punti di debolezza (nella prospettiva di prevenzione e repressione delle condotte illecite) della dimensione digitale del riciclaggio. – 6. L’evoluzione della disciplina di contrasto nei confronti del Cyberlaundering. I primi passi normativi per prevenire i rischi di riciclaggio nel mondo delle criptovalute. – 7. Considerazioni conclusive

Bioinspired motifs in proton and CO2 reduction with 3d-metal polypyridine complexes

The synthesis of active and efficient catalysts for solar fuel generation is nowadays of high relevance for the scientific community, but at the same time poses great challenges. Critical requirements are mainly associated with the kinetic barriers due to the multi-proton and multi-electron nature of the hydrogen evolution reaction (HER) and the CO2 reduction reaction (CO2RR) as well as to selectivity issues. In this regard, natural enzymes can be a source of inspiration for the design of effective and selective catalysts to target such fundamental reactions. In this Feature Article we review some recent works on molecular catalysts for both the HER and the CO2RR performed in our labs and other research teams which mainly address (i) the role of redox noninnocent ligands, to lower the overpotential for catalysis and control the selectivity, and (ii) the role of internal relays, to assist formation of catalytic intermediates via intramolecular routes. The selected exemplars have been chosen to emphasize that, although the molecular structures and the synthetic motifs are different from those of the active sites of natural enzymes, many affinities in terms of catalytic mechanism and functionality are instead present, which account for the observed remarkable performances under operative conditions. The data discussed herein thus demonstrate the great potential and the privileged role of molecular catalysts towards the design and construction of hybrid photochemical systems for solar energy conversion into fuels