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A 79-year-old man with a failed 25-mm CE Magna Ease 3300 surgical prosthesis (Edwards Lifesciences) and of high re-operative surgical risk (STS 8%) presented with dyspnea, NYHA III. Cardiac computed tomography angiography revealed anatomy that was high risk for coronary occlusion with a short right coronary artery height of 6 mm and a valve-to-coronary distance of 2 mm.

Recent American College of Cardiology (ACC), American Heart Association (AHA), American College of Clinical Pharmacy (ACCP), and Heart Rhythm Society (HRS) guidelines suggest that patients with atrial fibrillation (AF) at intermediate to low annual risk of ischemic stroke can benefit from consideration of factors that might modify their risk of stroke. The role of nontraditional risk factors, such as primary hyperparathyroidism (PHPT), remains unexplored. In our study, we investigated the potential association between PHPT and the risk of ischemic stroke in patients with AF. Using data from the Nationwide Inpatient Sample Database, a retrospective cohort study focused on the adult population with AF, we stratified the participants based on PHPT presence. Demographic information, co-morbidities, and hospitalization details were extracted using International Classification of Diseases, Tenth revision codes. Propensity score matching was applied, encompassing over 20 confounding variables, including the risk factors outlined in the CHA 2 DS 2 -VASc (Congestive heart failure (C), Hypertension (H), Age ≥75 years (A₂), Diabetes Mellitus (D), Stroke/Transient Ischemic Attack (TIA)/Thromboembolism (S₂), Vascular disease (V), Age 65-74 years (A), Sex category [female] (Sc)) score. Multivariate logistic regression analysis was performed after matching to assess the independent impact of PHPT as an ischemic stroke risk factor. A total of 2,051 of the identified 395,249 patients with AF had PHPT. The PHPT group had an average age of 74 years and consisted of more women (66.1% vs 53.0%). After matching, it was observed that the PHPT group had longer hospital stays (5 vs 4 days) and higher hospitalization charges ($45,126 vs $36,644). This group exhibited higher rates of ischemic stroke (6.0% vs 4.4%) and mortality (6.3% vs 4.9%). The adjusted outcomes showed a 1.4-fold increased risk for ischemic stroke and a 1.32-fold increased risk for mortality in the PHPT cohort. The subgroup analysis showed a higher incidence of mortality in men with a high CHA 2 DS 2 -VASc score. In conclusion, this study highlights a marked association between PHPT and ischemic stroke in patients with AF, independent of the conventional CHA 2 DS 2 -VASc score. The potential mechanisms implicated include vascular changes, cardiac dysfunction, and coagulation cascade alterations. The presence of PHPT should be taken into consideration when deciding the assessment of thromboembolic risk., Competing Interests: Declaration of competing interest The authors have no competing interest to declare., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Hemostasis for transfemoral transcatheter aortic valve replacement (TAVR) is typically achieved using a suture-mediated vascular closure device (VCD) prior to large-bore sheath insertion (preclosure technique). Recently, the addition of a hybrid closure technique using a preclose technique with the addition of a collagen-plug VCD after sheath removal in cases of failed hemostasis has been utilized., Methods: Data were collected from the Northwell TAVR registry, including 3 high-volume TAVR centers. We evaluated a preclose strategy with suture-mediated vascular closure alone ("legacy strategy") and standard bailout techniques versus a contemporary hybrid strategy of suture-mediated closure with collagen-mediated closure bailout. The primary end point was major or minor vascular complications as defined by the VARC-3 criteria., Results: A total of 1327 patients were included, of which 791 patients underwent TAVR with suture-mediated closure alone and 536 with contemporary strategy. The primary end point (major or minor vascular complication) was lower in the contemporary strategy (5.44% vs 1.31%; P < .001). Both minor (3.92% vs 1.12%; P = .002) and major (1.14% vs 0.19%; P = .0196) vascular complications were reduced and the total length of stay was less in the contemporary strategy (median of 3 days vs 2 days; P < .0001). Using multivariable analysis, we observed that vascular management strategy significantly improved the composite primary outcome when adjusted for sheath size, peripheral artery disease, carotid disease, and site of procedure. In the contemporary group, bailout collagen-plug VCD with an Angio-Seal (Terumo Medical) was used in 68 patients (12.69%) and bailout MANTA (Teleflex) was required in 4 patients (0.75%). There were no major or minor vascular complications among the patients who received bailout collagen-plug VCD., Conclusions: A contemporary hybrid strategy of suture-mediated closure with collagen-mediated closure bailout reduces the risk of vascular complications among patients undergoing transfemoral TAVR., (© 2024 Society for Cardiovascular Angiography and Interventions Foundation. Published by Elsevier Inc.)

Growing concern surrounds the impact of social media platforms on public discourse 1-4 and their influence on social dynamics 5-9 , especially in the context of toxicity 10-12 . Here, to better understand these phenomena, we use a comparative approach to isolate human behavioural patterns across multiple social media platforms. In particular, we analyse conversations in different online communities, focusing on identifying consistent patterns of toxic content. Drawing from an extensive dataset that spans eight platforms over 34 years-from Usenet to contemporary social media-our findings show consistent conversation patterns and user behaviour, irrespective of the platform, topic or time. Notably, although long conversations consistently exhibit higher toxicity, toxic language does not invariably discourage people from participating in a conversation, and toxicity does not necessarily escalate as discussions evolve. Our analysis suggests that debates and contrasting sentiments among users significantly contribute to more intense and hostile discussions. Moreover, the persistence of these patterns across three decades, despite changes in platforms and societal norms, underscores the pivotal role of human behaviour in shaping online discourse., (© 2024. The Author(s).)

In our efforts to develop inhibitors selective for neuronal nitric oxide synthase (nNOS) over endothelial nitric oxide synthase (eNOS), we found that nNOS can undergo conformational changes in response to inhibitor binding that does not readily occur in eNOS. One change involves movement of a conserved tyrosine, which hydrogen bonds to one of the heme propionates, but in the presence of an inhibitor, changes conformation, enabling part of the inhibitor to hydrogen bond with the heme propionate. This movement does not occur as readily in eNOS and may account for the reason why these inhibitors bind more tightly to nNOS. A second structural change occurs upon the binding of a second inhibitor molecule to nNOS, displacing the pterin cofactor. Binding of this second site inhibitor requires structural changes at the dimer interface, which also occurs more readily in nNOS than in eNOS. Here, we used a combination of crystallography, mutagenesis, and computational methods to better understand the structural basis for these differences in NOS inhibitor binding. Computational results show that a conserved tyrosine near the primary inhibitor binding site is anchored more tightly in eNOS than in nNOS, allowing for less flexibility of this residue. We also find that the inefficiency of eNOS to bind a second inhibitor molecule is likely due to the tighter dimer interface in eNOS compared with nNOS. This study provides a better understanding of how subtle structural differences in NOS isoforms can result in substantial dynamic differences that can be exploited in the development of isoform-selective inhibitors.

The role of social media in information dissemination and agenda-setting has significantly expanded in recent years. By offering real-time interactions, online platforms have become invaluable tools for studying societal responses to significant events as they unfold. However, online reactions to external developments are influenced by various factors, including the nature of the event and the online environment. This study examines the dynamics of public discourse on digital platforms to shed light on this issue. We analyzed over 12 million posts and news articles related to two significant events: the release of ChatGPT in 2022 and the global discussions about COVID-19 vaccines in 2021. Data was collected from multiple platforms, including Twitter, Facebook, Instagram, Reddit, YouTube, and GDELT. We employed topic modeling techniques to uncover the distinct thematic emphases on each platform, which reflect their specific features and target audiences. Additionally, sentiment analysis revealed various public perceptions regarding the topics studied. Lastly, we compared the evolution of engagement across platforms, unveiling unique patterns for the same topic. Notably, discussions about COVID-19 vaccines spread more rapidly due to the immediacy of the subject, while discussions about ChatGPT, despite its technological importance, propagated more gradually., (© 2024. The Author(s).)

The web radically changed the dissemination of information and the global spread of news. In this study, we aim to reconstruct the connectivity patterns within nations shaping news propagation globally in 2022. We do this by analyzing a dataset of unprecedented size, containing 140 million news articles from 183 countries and related to 37,802 domains in the GDELT database. Unlike previous research, we focus on the sequential mention of events across various countries, thus incorporating a temporal dimension into the analysis of news dissemination networks. Our results show a significant imbalance in online news spreading. We identify news superspreaders forming a tightly interconnected rich club, exerting significant influence on the global news agenda. To further investigate the mechanisms underlying news dissemination and the shaping of global public opinion, we model countries' interactions using a gravity model, incorporating economic, geographical, and cultural factors. Consistent with previous studies, we find that countries' GDP is one of the main drivers to shape the worldwide news agenda., (© 2024. The Author(s).)

Online social media foster the creation of active communities around shared narratives. Such communities may turn into incubators for conspiracy theories-some spreading violent messages that could sharpen the debate and potentially harm society. To face these phenomena, most social media platforms implemented moderation policies, ranging from posting warning labels up to deplatforming, i.e. permanently banning users. Assessing the effectiveness of content moderation is crucial for balancing societal safety while preserving the right to free speech. In this article, we compare the shift in behavior of users affected by the ban of two large communities on Reddit, GreatAwakening and FatPeopleHate , which were dedicated to spreading the QAnon conspiracy and body-shaming individuals, respectively. Following the ban, both communities partially migrated to Voat, an unmoderated Reddit clone. We estimate how many users migrate, finding that users in the conspiracy community are much more likely to leave Reddit altogether and join Voat. Then, we quantify the behavioral shift within Reddit and across Reddit and Voat by matching common users. While in general the activity of users is lower on the new platform, GreatAwakening users who decided to completely leave Reddit maintain a similar level of activity on Voat. Toxicity strongly increases on Voat in both communities. Finally, conspiracy users migrating from Reddit tend to recreate their previous social network on Voat. Our findings suggest that banning conspiracy communities hosting violent content should be carefully designed, as these communities may be more resilient to deplatforming., (© The Author(s) 2023. Published by Oxford University Press on behalf of National Academy of Sciences.)

Social media platforms heavily changed how users consume and digest information and, thus, how the popularity of topics evolves. In this paper, we explore the interplay between the virality of controversial topics and how they may trigger heated discussions and eventually increase users' polarization. We perform a quantitative analysis on Facebook by collecting ∼57M posts from ∼2M pages and groups between 2018 and 2022, focusing on engaging topics involving scandals, tragedies, and social and political issues. Using logistic functions, we quantitatively assess the evolution of these topics finding similar patterns in their engagement dynamics. Finally, we show that initial burstiness may predict the rise of users' future adverse reactions regardless of the discussed topic., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Etta et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Treatment of congestive heart failure (CHF) with left ventricular (LV) systolic dysfunction and severe aortic stenosis (AS) is challenging, yet transcatheter aortic valve replacement (TAVR) has emerged as a suitable treatment option in such patients. We compared the periprocedural outcomes of TAVR in patients with an ejection fraction (EF) of ≤20% (VLEF group) to patients with an EF > 20% to ≤40% (LEF group). We included patients with severe AS and reduced LV ejection fraction (LVEF ≤ 40%) who underwent TAVR at four centers within Northwell Health between January 2016 and December 2020. Over 2000 consecutive patients were analyzed, of which 355 patients met the inclusion criteria. The primary composite endpoint was in-hospital mortality, moderate or greater paravalvular (PVL), stroke, conversion to open surgery, aortic valve re-intervention, and/or need for PPM. Secondary endpoints were length of stay, NYHA classification at 1 month and 1 year, mortality at 1 month and 1 year, mean valve gradient at 1 month, KCCQ score at 1 month, and ≥ moderate PVL at 1 month. There was no difference in the primary composite endpoint between the two groups (23.6% for VLEF vs. 25.3% for LEF, p = 0.29). During TAVR placement, 40% of patients in the VLEF group required ≥1 vasopressors for hypotension lasting ≥30 min vs. only 21% of patients in the LEF group ( p < 0.01). Intra-aortic balloon pump (IABP) use during procedure was greater in the VLEF group (9% vs. 1%, p < 0.01)-all placed post TAVR. Emergency ECMO use was higher in the VLEF group as well (5% vs. 0%). Total length of stay was significantly different between the two groups as well (6 days vs. 3 days, p < 0.01). Both groups had a change in LVEF of ~10%. One-year outcomes were similar between the groups. All-cause mortality at 1 year was not significantly different at 1 year (13% for VLEF vs. 11% for LEF), and KCC scores were also similar (77.54 vs. 74.97). Mean aortic valve gradients were also similar (12 mmHg vs. 11 mmHg, p = 0.48). Our study suggests that patients with EF ≤ 20% can safely have TAVR with similar periprocedural outcomes compared to patients with EF > 20% to ≤40% despite higher rates of vasopressor and mechanical support.

The immune system plays a central role in the onset and progression of cancer. A better understanding of transcriptional changes in immune cell-related genes associated with cancer progression, and their significance in disease prognosis, is therefore needed. NanoString-based targeted gene expression profiling has advantages for deployment in a clinical setting over RNA-seq technologies. We analysed NanoString PanCancer Immune Profiling panel gene expression data encompassing 770 genes, and overall survival data, from multiple previous studies covering 10 different cancer types, including solid and blood malignancies, across 515 patients. This analysis revealed an immune gene signature comprising 39 genes that were upregulated in those patients with shorter overall survival; of these 39 genes, three (MAGEC2, SSX1 and ULBP2) were common to both solid and blood malignancies. Most of the genes identified have previously been reported as relevant in one or more cancer types. Using Cibersort, we investigated immune cell levels within individual cancer types and across groups of cancers, as well as in shorter and longer overall survival groups. Patients with shorter survival had a higher proportion of M2 macrophages and γδ T cells. Patients with longer overall survival had a higher proportion of CD8+ T cells, CD4+ T memory cells, NK cells and, unexpectedly, T regulatory cells. Using a transcriptomics platform with certain advantages for deployment in a clinical setting, our multi-cancer meta-analysis of immune gene expression and overall survival data has identified a specific transcriptional profile associated with poor overall survival., Competing Interests: The authors have declared that no competing interests exist., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

The COVID-19 pandemic made explicit the issues of communicating science in an information ecosystem dominated by social media platforms. One of the fundamental communication challenges of our time is to provide the public with reliable content and contrast misinformation. This paper investigates how social media can become an effective channel to promote engagement and (re)build trust. To measure the social response to quality communication, we conducted an experimental study to test a set of science communication recommendations on Facebook and Twitter. The experiment involved communication practitioners and social media managers from select countries in Europe, applying and testing such recommendations for five months. Here we analyse their feedback in terms of adoption and show that some differences emerge across platforms, topics, and recommendation categories. To evaluate these recommendations' effect on users, we measure their response to quality content, finding that the median engagement is generally higher, especially on Twitter. The results indicate that quality communication strategies may elicit positive feedback on social media. A data-driven and co-designed approach in developing counter-strategies is thus promising in tackling misinformation., Competing Interests: The authors have declared that no competing interests exist.

Conspiracy theories proliferate online. We provide an overview of information consumption patterns related to conspiracy content on four mainstream social media platforms (Facebook, Twitter, YouTube, and Reddit), with a focus on niche ones. Opinion polarisation and echo chambers appear as pivotal elements of communication around conspiracy theories. A relevant role may also be played by the content moderation policies enforced by each social media platform. Banning contents or users from a social media could lead to a level of user segregation that goes beyond echo chambers and reaches the entire social media space, up to the formation of 'echo platforms'. The insurgence of echo platforms is a new online phenomenon that needs to be investigated as it could foster many dangerous phenomena that we observe online, including the spreading of conspiracy theories., Competing Interests: Conflict of interest statement Nothing declared., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Background: Cyclin-dependent kinase 4/6 inhibitors (CDK4/6 i), abemaciclib, palbociclib, and ribociclib, have been FDA-approved for the treatment of hormone receptor-positive (HR+), HER2−negative (HER2−) advanced breast cancer (aBC). This targeted therapy has revived hope in those aBC patients who did not respond to standard therapies. Interestingly, when administered as a single agent, CDK4/6 modulated several peripheral blood cells after a short-course treatment of 28 days. However, the impact of these immune effects has yet to be thoroughly investigated. Methods: We administered abemaciclib, palbociclib, and ribociclib monotherapy to 23 patients with HR+/HER2− metastatic breast cancer. The aim is to investigate the impact of on-treatment modifications on peripheral blood cells and their composite scores in patients after a 28-day course of CDK4/6 i alone. Results: In the current study, we observed a significant decrease in neutrophils (p-value < 0.001) for patients treated with abemaciclib, palbociclib, and ribociclib. An overall decrease of Tregs was observed and potentially linked to palbociclib treatment. The neutrophile to lymphocyte (N/L) ratio was also decreased overall and potentially linked to abemaciclib and palbociclib treatment. Platelets were decreased in patients administered with abemaciclib. Notably, the radiometabolic response was available only for those patients treated with ribociclib and abemaciclib, and only those lesions treated with ribociclib reached statistical relevance. Conclusions: Our study strongly supports the notion that CDK4/6 inhibitors induce tumour immune modulation. N/L ratio and platelet levels decreased due to treatment. Future studies should test whether patients would benefit from immunomodulators in association with CDK4/6 agents in a larger clinical trial. Moreover, the CDK4/6-induced immune modulation could also be considered a potential predictive clinical factor in HR+/HER2− advanced breast cancer.

Background: Traditional open sternotomy coronary artery bypass grafting (CABG) utilizes highly invasive techniques that lead to several serious complications. In response, minimally invasive cardiac surgery CABG (MICS-CABG) was developed. MICS-CABG is safe, reproducible, and with fewer complications, while allowing for better postoperative recovery periods. There is a paucity of data exploring rates of repeat revascularization in patients post MICS-CABG compared to post traditional sternotomy CABG., Methods: This was a retrospective billing database review examining 1468 CABG patients at a large university medical center from January 2005 to December 2017. The primary objective was to compare the rate of repeat revascularization events between MICS-CABG and traditional open sternotomy CABG over an eight-year follow-up period., Results: Our study population consisted of 1468 patients, of whom 513 had MICS-CABG and 955 had traditional CABG. The number of patients undergoing repeat revascularization within the eight-year surveillance was 99 for MICS-CABG and 75 for traditional CABG. The Kaplan-Meier survival probability estimates for eight years were 0.86 for MICS-CABG and 0.91 for traditional CABG. The mean time until a repeat revascularization event was 84.1 months for MICS-CABG and 88.5 months for traditional CABG., Conclusions:  Traditional CABG was found to have a statistically significantly longer time to repeat revascularization than MICS-CABG. Despite the technical challenges associated with MICS-CABG, the time to repeat revascularization was different by only about four months, which may not hold large clinical significance. This suggests that MICS-CABG may have a role to play due to previous findings showing a reduction in complications while allowing for better postoperative recovery periods., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2022, Olson et al.)

The concept of resilience-i.e., the ability of a unified structure to absorb shocks-is of high relevance in the context of network modelling and analysis, mainly when referred to finance. This paper starts from this premise, and deals with the resilience of a financial interbanking system. At this aim, we firstly introduce a new measure of the resilience of a network, by taking into full consideration the influence of the topology of the network and the weights of its links in the shocks propagation; then, we build one financial network model related to the quarterly-based interbanking sector, whose weights are calibrated on high quality empirical data; lastly, we compute the resilience measure of the considered networks. A discussion of the results is provided, by considering both finance and network theory perspectives., (© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022.)

Background: Individuals who have sustained a concussion often display associated balance control deficits and visuomotor impairments despite being cleared by a physician to return to sport. Such visuomotor impairments can be highlighted in collision avoidance tasks that involves a mutual adaptation between two walkers. However, studies have yet to challenged athletes with a previous concussion during an everyday collision avoidance task, following return to sport., Research Question: Do athletes with a previous concussion display associated behavioural changes during a 90°-collision avoidance task with an approaching pedestrian?, Methods: Thirteen athletes (ATH; 9 females, 23 ± 4years) and 13 athletes with a previous concussion (CONC; 9 females, 22 ± 3 years, concussion <6 months) walked at a comfortable walking speed along a 12.6 m pathway while avoiding another athlete on a 90º-collision course. Each participant randomly interacted with individuals from the same group 20 times and interacted with individuals from the opposite group 21 times. Minimum predicted distance (mpd) was used to examine collision avoidance behaviours between ATH and CONC groups., Results: The overall progression of mpd(t) did not differ between groups (p > .05). During the collision avoidance task, previously concussed athletes contributed less when passing second compared to their peers(p < .001). When two previously concussed athletes were on a collision course, there was a greater amount of variability resulting in inappropriate adaptive behaviours., Significance: Although successful at avoiding a collision with an approaching athlete, previously concussed athletes exhibit behavioural changes manifesting in riskier behaviours. The current findings suggest that previously concussed athletes possess behavioural changes even after being cleared to returned to sport, which may increase their risk of a subsequent injury when playing., (Copyright © 2021 Elsevier B.V. All rights reserved.)

The COVID-19 information epidemic, or "infodemic," demonstrates how unlimited access to information may confuse and influence behaviors during a health emergency. However, the study of infodemics is relatively new, and little is known about their relationship with epidemics management. Here, we discuss unresolved issues and propose research directions to enhance preparedness for future health crises., Competing Interests: Declaration of Interests The authors declare no competing interests., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Online debates are often characterised by extreme polarisation and heated discussions among users. The presence of hate speech online is becoming increasingly problematic, making necessary the development of appropriate countermeasures. In this work, we perform hate speech detection on a corpus of more than one million comments on YouTube videos through a machine learning model, trained and fine-tuned on a large set of hand-annotated data. Our analysis shows that there is no evidence of the presence of "pure haters", meant as active users posting exclusively hateful comments. Moreover, coherently with the echo chamber hypothesis, we find that users skewed towards one of the two categories of video channels (questionable, reliable) are more prone to use inappropriate, violent, or hateful language within their opponents' community. Interestingly, users loyal to reliable sources use on average a more toxic language than their counterpart. Finally, we find that the overall toxicity of the discussion increases with its length, measured both in terms of the number of comments and time. Our results show that, coherently with Godwin's law, online debates tend to degenerate towards increasingly toxic exchanges of views., (© 2021. The Author(s).)

On the Internet, information circulates fast and widely, and the form of content adapts to comply with users' cognitive abilities. Memes are an emerging aspect of the internet system of signification, and their visual schemes evolve by adapting to a heterogeneous context. A fundamental question is whether they present culturally and temporally transcendent characteristics in their organizing principles. In this work, we study the evolution of 2 million visual memes published on Reddit over ten years, from 2011 to 2020, in terms of their statistical complexity and entropy. A combination of a deep neural network and a clustering algorithm is used to group memes according to the underlying templates. The grouping of memes is the cornerstone to trace the growth curve of these objects. We observe an exponential growth of the number of new created templates with a doubling time of approximately 6 months, and find that long-lasting templates are associated with strong early adoption. Notably, the creation of new memes is accompanied with an increased visual complexity of memes content, in a continuous effort to represent social trends and attitudes, that parallels a trend observed also in painting art., (© 2021. The Author(s).)

This study proposes a set of key decision-making features of the contaminated site remediation process to assist in selecting the most appropriate decision support method(s). Using a case study consistent with the requirements of the U.S. regulation for contaminated sites management, this article shows that suitable Multiple Criteria Decision Analysis methods can be selected based on a dynamic and evolving problem structuring. The selected methods belong to the family of PROMETHEE methods and can provide ranking recommendations of the considered alternatives using variable structures of the criteria, evaluation of the alternatives and exploitation of the preference model. It was found that in order to support a quick and up-to-date application of powerful decision support techniques in the process of remediation of contaminated sites, decision analysts and stakeholders should interact and co-develop the process. This research also displays how such interactions can guarantee a transparent and traceable decision recommendation so that stakeholders can better understand why some alternatives perform comprehensively better than others when a multitude of inputs is used in the decision-making process.

The COVID-19 pandemic is one of the defining events of our time. National Governments responded to the global crisis by implementing mobility restrictions to slow down the spread of the virus. To assess the impact of those policies on human mobility, we perform a massive comparative analysis on geolocalized data from 13 M Facebook users in France, Italy, and the UK. We find that lockdown generally affects national mobility efficiency and smallworldness-i.e., a substantial reduction of long-range connections in favor of local paths. The impact, however, differs among nations according to their mobility infrastructure. We find that mobility is more concentrated in France and UK and more distributed in Italy. In this paper we provide a framework to quantify the substantial impact of the mobility restrictions. We introduce a percolation model mimicking mobility network disruption and find that node persistence in the percolation process is significantly correlated with the economic and demographic characteristics of countries: areas showing higher resilience to mobility disruptions are those where Value Added per Capita and Population Density are high. Our methods and findings provide important insights to enhance preparedness for global critical events and to incorporate resilience as a relevant dimension to estimate the socio-economic consequences of mobility restriction policies.

Background: To date (April 2021), medical device (MD) design approaches have failed to consider the contexts where MDs can be operationalised. Although most of the global population lives and is treated in Low- and Middle-Income Countries (LMCIs), over 80% of the MD market share is in high-resource settings, which set de facto standards that cannot be taken for granted in lower resource settings. Using a MD designed for high-resource settings in LMICs may hinder its safe and efficient operationalisation. In the literature, many criteria for frameworks to support resilient MD design were presented. However, since the available criteria (as of 2021) are far from being consensual and comprehensive, the aim of this study is to raise awareness about such challenges and to scope experts' consensus regarding the essentiality of MD design criteria., Results: This paper presents a novel application of Delphi study and Multiple Criteria Decision Analysis (MCDA) to develop a framework comprising 26 essential criteria, which were evaluated and chosen by international experts coming from different parts of the world. This framework was validated by analysing some MDs presented in the WHO Compendium of innovative health technologies for low-resource settings., Conclusions: This novel holistic framework takes into account some domains that are usually underestimated by MDs designers. For this reason, it can be used by experts designing MDs resilient to low-resource settings and it can also assist policymakers and non-governmental organisations in shaping the future of global healthcare.

The paper contributes to the debate concerning the management of municipal solid waste by providing an analysis of two key aspects of waste management - namely, waste separation and dispatch to treatment plants. Our analysis aims at detecting the extent to which actual behavior in (close-by) municipalities is similar with respect to those two aspects. To pursue our scope, a complex network approach is followed. In particular, we conceptualize, explore and compare two networks, whose nodes are the municipalities, while weights synthesize in one network the percentage of sorted waste that is collected at a municipal level, and in the other one the distance from the waste processing plants used by each municipality. The theoretical network models are implemented through an empirical study based on a high quality dataset referred to Italian municipalities. In this regard, the detection of communities of municipalities and their geospatial contextualization are introduced as devices for a complete description of current practices of municipal waste separation and transfers in Italy., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Social media may limit the exposure to diverse perspectives and favor the formation of groups of like-minded users framing and reinforcing a shared narrative, that is, echo chambers. However, the interaction paradigms among users and feed algorithms greatly vary across social media platforms. This paper explores the key differences between the main social media platforms and how they are likely to influence information spreading and echo chambers' formation. We perform a comparative analysis of more than 100 million pieces of content concerning several controversial topics (e.g., gun control, vaccination, abortion) from Gab, Facebook, Reddit, and Twitter. We quantify echo chambers over social media by two main ingredients: 1) homophily in the interaction networks and 2) bias in the information diffusion toward like-minded peers. Our results show that the aggregation of users in homophilic clusters dominate online interactions on Facebook and Twitter. We conclude the paper by directly comparing news consumption on Facebook and Reddit, finding higher segregation on Facebook., Competing Interests: The authors declare no competing interest., (Copyright © 2021 the Author(s). Published by PNAS.)

Since its emergence in late 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a pandemic with more than 55 million reported cases and 1.3 million estimated deaths worldwide. While epidemiological and clinical characteristics of COVID-19 have been reported, risk factors underlying the transition from mild to severe disease among patients remain poorly understood. In this retrospective study, we analysed data of 879 confirmed SARS-CoV-2 positive patients admitted to a two-site NHS Trust hospital in London, England, between January 1st and May 26th, 2020, with a majority of cases occurring in March and April. We extracted anonymised demographic data, physiological clinical variables and laboratory results from electronic healthcare records (EHR) and applied multivariate logistic regression, random forest and extreme gradient boosted trees. To evaluate the potential for early risk assessment, we used data available during patients' initial presentation at the emergency department (ED) to predict deterioration to one of three clinical endpoints in the remainder of the hospital stay: admission to intensive care, need for invasive mechanical ventilation and in-hospital mortality. Based on the trained models, we extracted the most informative clinical features in determining these patient trajectories. Considering our inclusion criteria, we have identified 129 of 879 (15%) patients that required intensive care, 62 of 878 (7%) patients needing mechanical ventilation, and 193 of 619 (31%) cases of in-hospital mortality. Our models learned successfully from early clinical data and predicted clinical endpoints with high accuracy, the best model achieving area under the receiver operating characteristic (AUC-ROC) scores of 0.76 to 0.87 (F1 scores of 0.42-0.60). Younger patient age was associated with an increased risk of receiving intensive care and ventilation, but lower risk of mortality. Clinical indicators of a patient's oxygen supply and selected laboratory results, such as blood lactate and creatinine levels, were most predictive of COVID-19 patient trajectories. Among COVID-19 patients machine learning can aid in the early identification of those with a poor prognosis, using EHR data collected during a patient's first presentation at ED. Patient age and measures of oxygenation status during ED stay are primary indicators of poor patient outcomes.