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Patients with Marfan syndrome often have severe life-threatening cardiovascular complications, including aortic aneurysmal dilatation or aortic dissection. Approximately two-thirds of people who have this syndrome suffer from chest wall deformities such as pectus excavatum (cobbler's chest) or pectus carinatum (bird's chest). When a patient with cobbler's chest requires aortic root surgery, the operator may face a major clinical challenge in selecting the optimal surgical access and approach. We present a case of a patient with Marfan syndrome and severe pectus excavatum who underwent aortic valve replacement, aortic root and ascending aorta reconstruction, coronary artery reimplantation (Bentall de Bono procedure ) via upper partial L-sternotomy and anterior left thoracotomy.

Introduction The EXPERIENCE project aims to enable the creation and sharing of extended-personal realities in virtual reality (VR). Currently, software and hardware technology are under development, that will automatically generate VR environments based on neurophysiological, psychological, cognitive, and behavioral data to support not only the recording of personal experiences but the transmission as well to another user. Potential use cases include enhanced treatment and the assessment of symptom severity of affective disorders. Objectives The objective is to design and create a virtual reality environment that enables the identification of between-group differences in behavioral measures when comparing depressed and healthy-control participants. Methods We conducted a literature review to identify measures that can be implemented in VR and have the potential to show differences between depressed and healthy-control participants. PubMed and ResearchGate databases were screened to identify potential cognitive tasks. A selection protocol was developed considering effect size, homogeneity of results, risk for cybersickness, cognitive demand, domain heterogeneity, and VR compatibility to choose 4 out of the 47 initial tasks. In addition to the cognitive tasks, behavior measures were considered as well and a virtual environment has been equipped to assess (1) exploratory behavior; (2) engagement with emotionally valenced stimuli (via eye-tracking); (3) metacognitive sensitivity, (4) persistence/grit, and (5) possible effects of mood induction. Results Based on the above review, a virtual environment has been developed which is composed of four rooms and a hallway where the starting point is. After an initial tutorial on how the environment/controllers work participants are free to explore and instructions are only provided for the specific cognitive tasks which have to be solved to open the doors and move between rooms. The rooms are equipped with numerous interactive objects and images with varying emotional valence. The engagement with the environment and general activity are continuously recorded and can be retrieved for analyses after participants exit the environment. Conclusions If the controlled VR environment will be proven effective for the assessment of depressive symptoms in future studies, the EXPERIENCE system could incorporate direct and objective behavioral measures into the assessment depressive symptoms. Consequently, the system has the potential to support the clinical diagnosis of affective disorders. Acknowledgement The EXPERIENCE project is funded by the European Commission H2020 Framework Program with the Grant No. 101017727. Disclosure of Interest None Declared

Abstract Introduction The final aim of the EXPERIENCE project is to enable individuals to record and share extended-personal realities in Virtual Reality (VR) - which entails the consideration of a person’s neurophysiological, psychological, and cognitive states. One prospective application is using this technology to aid in assessing symptoms of affective disorders. Objectives The objective is to test the ability of a pre-designed VR environment to differentiate between individuals with depressive symptoms and healthy controls (HCs) via machine learning algorithms. Methods Conducted as a pilot study in Italy, we recruited 100 volunteers, comprising 50 HCs and 50 individuals with moderate depressive symptoms assessed via the PHQ-9. Through a 40–60-minute VR engagement, comprehensive data on cognitive (inc. cognitive flexibility, sustained attention, working memory, processing speed), behavioral (exploration, attentional bias), and physiological (heart-rate variability, skin conductance) variables was collected. Subsequently, an explainable artificial intelligence model (xAI) was trained on data from 80% of the sample and tested on the remaining 20% in terms of accuracy for between-group classification. Results Following an iterative process that considered both the importance assigned to each variable in the different models and the theoretical relevance of these variables to depression the final model achieved an average accuracy of 71% (with individual trials ranging from 64.5% to 77.1%). Key predictors included exploratory behaviors and heart-rate variability during both exploration and cognitive tasks. Conclusions These results are comparable, however remain below the levels of accuracy achieved based on fMRI and DTI data alone (around 80%). Nonetheless, the EXPERIENCE system, slated for refinement beyond this pilot phase, shows potential in integrating multimodal data for evaluating affective disorder symptoms, aiming for a more objective screening and diagnostic approach at a lower cost. Acknowledgement The EXPERIENCE project is funded by the European Commission H2020 Framework Program, Grant No. 101017727. Disclosure of Interest None Declared

Climate Change and Materials Criticality challenges are driving urgent responses from global governments. These global responses drive policy to achieve sustainable, resilient, clean solutions with Advanced Materials (AdMats) for industrial supply chains and economic prosperity. The research landscape comprising industry, academe, and government identified a critical path to accelerate the Green Transition far beyond slow conventional research through Digital Technologies that harness Artificial Intelligence, Smart Automation and High Performance Computing through Materials Acceleration Platforms, MAPs. In this perspective, following the short paper, a broad overview about the challenges addressed, existing projects and building blocks of MAPs will be provided while concluding with a review of the remaining gaps and measures to overcome them., (© 2024 The Author(s). Advanced Materials published by Wiley‐VCH GmbH.)

Self-monitoring with support, lifestyle modifications, and emotion management improves blood pressure (BP). Patients with hypertension need continual support to modify behaviors, but time pressures limit lifestyle education in primary care settings. Using mixed methods, we aimed to study the feasibility and acceptability of an innovative 6-week program that combined self-monitoring with coping skills and lifestyle education for patients with uncontrolled hypertension. Patients with uncontrolled hypertension interested in lifestyle modifications before intensifying medications were enrolled from primary care clinics. Patients self-monitored emotions, behaviors, and BPs and received education from medical providers and mind-body therapists through shared medical appointments (SMAs) with an option of weekly printed materials. Over 6 months, 31 eligible participants completed the program with higher uptake (21/41) from physician referrals (74.2% women, 41.9% Black, median household income $100 000). Fourteen participants opted for weekly educational materials due to upcoming SMA sessions being fully booked or personal schedules. Pre- to post-intervention paired t-test showed improvement in systolic BP of 11.6 mmHg (95% CI, 6.6-16.6, p < 0.0001), and hypertension control rate improved by 36% (11/31) post-intervention. Higher baseline systolic BP was associated with higher BP reduction (p < 0.001). Thematic analysis showed the perceived benefit of self-awareness, education, and peer support, whereas time constraints were perceived as challenges. Self-monitoring with education on coping skills and lifestyle modification is feasible and improved BP and hypertension control across diverse primary care patients interested in lifestyle modifications; however, few low-income patients enrolled. Less burdensome and community-based interventions may improve participation in low-income patients., (© 2024 The Author(s). The Journal of Clinical Hypertension published by Wiley Periodicals LLC.)

Introduction: Obstructive jaundice is a clinical syndrome that is commonly seen in gastroenterology. Endoscopic retrograde cholangiopancreatography (ERCP) has been recognized as a first-choice therapeutic approach, with percutaneous biliary interventions (PBIs) being a viable alternative. Recent data questions the performance and safety profile of PBIs., (This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: In 2020 and 2021, chalcidoid parasitoids (Hymenoptera, Chalcidoidea) of bark beetles in pine ( Pinus spp.) plantations were studied in Bulgaria. Samples (cuttings of stems and branches) of pine trees infested by bark beetles were collected from seven plantations of Pinussylvestris and P.nigra in Bulgaria. From each sampling plot, five cuttings were collected and placed in photoeclectors in laboratory conditions (18-22ºC). Emerged bark beetles and parasitoids were regularly gathered and fixed in ethanol., New Information: Six parasitoid species - Dinotiscuscolon , Metacolusazureus , M.unifasciatus , Rhopalicusquadratus , R.tutela (Chalcidoidea: Pteromalidae) and Heydeniapretiosa (Chalcidoidea, Heydeniidae) were reared from five bark beetle hosts ( Ipsacuminatus , Pityogenesbistridentatus , Pityophthoruspityographus , Tomicuspiniperda and T.minor ). Amongst them, three species ( H.pretiosa , M.azureus and R.quadratus ) are recorded as new for Bulgarian fauna., (Sevdalin Belilov, Ivaylo Todorov, Margarita Georgieva, Georgi Georgiev.)

Graphene-cellulose interactions have considerable potential in the development of new materials. In previous computational work (Biomacromolecules2016, 16, 1771), we predicted that the model 100 hydrophobic surface of cellulose interacted favourably with pristine graphene in aqueous solution molecular dynamics simulations; conversely, a model of the hydrophilic 010 surface of cellulose exhibited progressive rearrangement to present a more hydrophobic face with the graphene, with weakened hydrogen bonds between cellulose chains and partial permeation of water. Here, we extend this work by simulating the interaction in aqueous solution of the amphiphilic 110 surface of a cellulose Iβ microfibril model, comprising 36 chains of 40 glucosyl residues, with an infinite sheet of pristine graphene. This face of the microfibril is of intermediate hydrophilicity and progressively associates with graphene over replicate simulations. As cellulose chains adhere to the graphene surface, forming interactions via its CH and OH groups, we observe a degree of local and global untwisting of the microfibril. Complementary rippling of the graphene surface is also observed, as it adapts to interaction with the microfibril. This adsorption process is accompanied by increased exclusion of water between cellulose and graphene although some water localises between chains at the immediate interface. The predicted propensity of a cellulose microfibril to adsorb spontaneously on the graphene surface, with mutual structural accommodation, highlights the amphiphilic nature of cellulose and the types of interactions that can be harnessed to design new graphene-carbohydrate biopolymer materials., 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 © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Quasi-elastic neutron scattering (QENS) and molecular dynamics (MD) simulations are applied in combination to investigate the dynamics of methane in H-ZSM-5 zeolite catalysts used for methanol-to-hydrocarbons reactions. Methane is employed as an inert model for the methanol reaction feedstock, and studies are made of the fresh catalyst and used catalysts with varying levels of coke buildup to investigate the effect of coking on reactant mobility. Measurements are made in the temperature range from 5 to 373 K. Methane mobility under these conditions is found to be extremely high in fresh ZSM-5, with the majority of movements occurring too fast to be resolved by the QENS instrument used. A small fraction of molecules undergoing jump diffusion on QENS time scales is identified and found to correspond with short-range jump diffusion within single zeolite pores as identified in MD simulations. Agreement between QENS and MD mobility measurements is found to be within 50%, validating the simulation approach employed. Methane diffusion is found to be minimally affected by moderate levels of coke buildup, while highly coked samples result in the confinement of methane to single pores within the zeolite with minimal long-range diffusion.

This European Materials Modelling Council (EMMC) study provides an outline of the survey intent and ambitions, followed by an analysis of the results and a follow up discussion, focused on the future perspectives of the EMMC. The survey covers materials modelling and characterisation communities in both academia and industry. It provides a profile of the surveyed players in these communities and a scaled measure on their usage of computational methodologies. The survey outcomes include: (i) summary views of the recent as well as perceived future trends of materials modelling and its associated fields, with respect to two focus areas surveyed, Model Development and Software, (ii) the main adoption factors and associated bottlenecks for computational methods and software, (iii) the most targeted materials properties and digital twins approaches, and (iv) the wider communities expectations of how EMMC can help facilitate, fulfil and drive further the European Materials Modelling Roadmap to the benefit of the European Commission's (ECs') research and innovation., Competing Interests: No competing interests were disclosed., (Copyright: © 2022 Todorov I.)