Athens Technology Center (Greece)

ABSTRACT We describe here various ion activation experiments realized in the Omnitrap™ platform integrated on the timsOmni TM mass spectrometer for the analysis of oligonucleotides in the negative ion mode. The activation methods include resonance collision-induced dissociation ( R CID), electron detachment dissociation (EDD), infrared laser multiple-photon activation (IRMPD) and UV laser photodissociation (UVPD). Special emphasis is given to EDD, either as a standalone technique or in conjunction with vibrational re-activation of the ion radicals. We describe EDD on standard 6-mer DNA sequences that have been extensively characterized on other instruments, followed by a comparison of several activation approaches for the phosphorothioate-based oligonucleotide therapeutics Fomivirsen, and concluding with the fragmentation analysis of 46-mer DNA and RNA. EDD alone already provides excellent sequence information on Fomivirsen, but MS 3 combinations such as EDD- R CID or EDD-IRMPD proved even more effective, including for the 46-mer DNA (less prone to fragmentation than RNA) at a relatively low charge state. The diversity of ion activation combinations available on the Omnitrap platform is demonstrated by an MS 4 experiment investigating the fate of a • and z • radical fragments produced by EDD. TOC graphics

This study demonstrates a data-driven decision support system to aid in rectification of prosthetic sockets aimed at improving overall comfort perceived by amputees. Prosthetic technology, particularly in the realm of socket design, plays a pivotal role in rehabilitation for individuals with limb amputations. Prosthetic sockets, which serve as the critical interface between the residual limb and the artificial limb, enable amputees to walk without the need for invasive implants that connect directly to the bone of the residual limb. This study focuses on the role of intra-socket pressure in socket performance and its impact on optimal socket rectifications for improving comfort in transfemoral amputees. Employing thin Force Sensing Resistor (FSR) sensors, the research measures dynamic pressure variations across individual gait cycles. To explore the effects of altered pressure distribution on socket performance, a clinical trial was conducted consisting of four different socket configurations across several participants, one of which was with no pad inserted and three of which incorporated a silicone pad to modify the dynamic pressure profiles. With data from multiple participants including specific dynamic pressure features extracted from FSR sensors, and subjective feedback of comfort, a Multi-Layer Perceptron (MLP) model is trained to establish predictive relationships between intra-socket pressure and appropriate rectification action. The findings suggest that the MLP agent is more accurate at suggesting rectification actions to prosthetists when compared to simpler classification algorithms such as Random Forest, XGBoost and Logistic regression, laying the foundation for future advancements in prosthetic design.

SAF 2507, a superduplex stainless steel, combines mechanical strength with high corrosion resistance. As a powder, it can be used in conjunction with the laser cladding deposition process (LCD), restoring damaged components by erosion and improving their properties, regarding surface hardness and resistance to corrosive environments. In the current study, a SAF 2507 powder was employed to fabricate various multi-pass clads on an austenitic 316 L substrate via laser cladding deposition (LCD). Specimens were later subjected to heat treatment procedures, in order to restore the phase balance ratio. The attained microstructures were observed through light optical and scanning electron microscopy (LOM and SEM), coupled with energy-dispersive spectroscopy (EDS) analysis. Vickers hardness tests were also conducted in order to evaluate the hardness of every clad layer. Finally, X-Ray Diffraction (XRD) was employed in order to ascertain the experimental results, as well as investigate the existence of undesirable phases. While a mostly ferritic microstructure was anticipated after the LCD process, the resulting clads were characterized by a relatively balanced phase ratio, with austenite being the dominant phase instead. After heat-treating, further austenite growth occurred, leading to an overall decrease in hardness, although nitrides that had precipitated during the deposition were no were no longer present.

Abstract This study presents the evaluation results of the “ATANA” research program, which focuses on a platform that integrates the creation and management of narratives associated with cultural tourism applications. Considering the objectives of this study and the target audience, the proposed method could be beneficial to museums and cultural institutions by providing interactive tours and enhancing the overall visitor experience. Additionally, it can be advantageous for cultural tourism stakeholders and local businesses in the surrounding areas as it may attract more tourists and increase footfall. The platform leverages augmented reality and narrative techniques within an ambient-intelligence environment that encompasses a museum and its surrounding landmarks. The case study pertains to the Kotsanas Museum of Ancient Greek Technology (MAET), an institution with a continuous presence for 25 years, represented through a network of museums on the same theme located in Ancient Olympia and Athens, and an exhibition in which the organisation has participated in Malta. The methodology employed leverages the principles of ambient intelligence, enabling tourists to traverse the historic centre of Athens or the archaeological site of the Olympia, and to explore ancient Greek technological inventions through a mobile application supporting augmented reality. The proposed approach also supported the participation of MAET in an exhibition in Malta by projecting a variety of 3D inventions presented in MAET museums through augmented reality.

Far-infrared radiation (FIR) has been investigated for reduction of pain and improvement of dermal blood flow. The FIRTECH patch is a medical device designed to re-emit FIR radiated by the body. This phase 1 study was conducted to evaluate the local effects of the FIRTECH patch on local skin perfusion, microcirculation and oxygenation. This prospective, randomized, open-label, parallel designed study admitted 20 healthy participants to a medical research facility for treatment for 31 h on three anatomical locations. During treatment, imaging assessments consisting of laser speckle contrast imaging, near-infrared spectroscopy, side-stream dark-field microscopy, multispectral imaging and thermography were conducted regularly on patch-treated skin and contralateral non-treated skin. The primary endpoint was baseline perfusion increase during treatment on the upper back. Secondary endpoints included change in baseline perfusion, oxygen consumption and temperature of treated versus untreated areas. The primary endpoint was not statistically significantly different between treated and non-treated areas. The secondary endpoints baseline perfusion on the forearm (least square means [LSMs] difference 2.63 PU, 95% CI: 0.97, 4.28), oxygen consumption (LSMs difference: 0.42 arbitrary units [AUs], 95% CI: 0.04, 0.81) and skin temperature (LSMs difference 0.35°C, 95% CI: 0.16, 0.6) were statistically significantly higher in treated areas. Adverse events observed during the study were mild and transient. The vascular response to the FIRTECH patch was short-lived suggesting a non-thermal vasodilatory effect of the patch. The FIRTECH patch was well tolerated, with mild and transient adverse events observed during the study. These results support the therapeutic potential of FIR in future investigations.

Tailoring personalized treatments demands the analysis of a patient’s characteristics, which may be scattered over a wide variety of sources. These features include family history, life habits, comorbidities, and potential treatment side effects. Moreover, the analysis of the services visited the most by a patient before a new diagnosis, as well as the type of requested tests, may uncover patterns that contribute to earlier disease detection and treatment effectiveness. Built on knowledge-driven ecosystems, we devise DE4LungCancer, a health data ecosystem of data sources for lung cancer. In this data ecosystem, knowledge extracted from heterogeneous sources, e.g., clinical records, scientific publications, and pharmacological data, is integrated into knowledge graphs. Ontologies describe the meaning of the combined data, and mapping rules enable the declarative definition of the transformation and integration processes. DE4LungCancer is assessed regarding the methods followed for data quality assessment and curation. Lastly, the role of controlled vocabularies and ontologies in health data management is discussed, as well as their impact on transparent knowledge extraction and analytics. This paper presents the lessons learned in the DE4LungCancer development. It demonstrates the transparency level supported by the proposed knowledge-driven ecosystem, in the context of the lung cancer pilots of the EU H2020-funded project BigMedilytic, the ERA PerMed funded project P4-LUCAT, and the EU H2020 projects CLARIFY and iASiS.

Nanomechanical mass spectrometry allows characterization of analytes with broad mass range, from small proteins to bacterial cells, and with unprecedented mass sensitivity. In this work, we show a novel multifrequency nanomechanical mass spectrometer prototype designed for focusing, guiding and soft-landing of nanoparticles and viral particles on a nanomechanical resonator surface placed in vacuum. The system is compatible with optomechanical disk resonators, with an integrated optomechanical transduction method, and with the laser beam deflection technique for the measurement of the vibrations of microcantilever resonators. The prototype allows the in-vacuum alignment of resonators thanks to a dedicated visualization system. Finally, in this work, we have demonstrated the detection of gold nanoparticles, polystyrene nanoparticles and phage G viruses with optomechanical disks and microcantilever resonators.

Scientific and clinical research have advanced the ability of healthcare professionals to more precisely define diseases and classify patients into different groups based on their likelihood of responding to a given treatment, and on their future risks. However, a significant gap remains between the delivery of stratified healthcare and personalization. The latter implies solutions that seek to treat each citizen as a truly unique individual, as opposed to a member of a group with whom they share common risks or health-related characteristics. Personalisation also implies an approach that takes into account personal characteristics and conditions of individuals. This paper investigates how these desirable attributes can be developed and introduces a holistic environment, the iHELP, that incorporates big data management and Artificial Intelligence (AI) approaches to enable the realization of data-driven pathways where awareness, care and decision support is provided based on person-centric early risk prediction, prevention and intervention measures.