Foundation for Research and Technology - Hellas

Alzheimer’s Disease (AD) is an incurable and debilitating progressive, neurodegenerative disorder which is the leading cause of dementia worldwide. Neuropathologically, AD is characterized by the accumulation of Aβ amyloid plaques in the microenvironment of brain cells and neurovascular walls, chronic neuroinflammation, resulting in neuronal and synaptic loss, myelin and axonal failure, as well as significant reduction in adult hippocampal neurogenesis. The hippocampal formation is particularly vulnerable to this degenerative process, due to early dysfunction of the cholinergic circuit. Neurotrophic factors consist major regulatory molecules and their decline in AD is considered as an important cause of disease onset and progression. Novel pharmacological approaches are targeting the downstream pathways controlled by neurotrophins, such as nerve growth factor (NGF) receptors, TrkA and p75NTR, which enhance hippocampal neurogenic capacity and neuroprotective mechanisms, and potentially counteract the neurotoxic effects of amyloid deposition. BNN27 is a non-toxic, newly developed 17-spiro-steroid analog, penetrating the blood-brain-barrier (BBB) and mimicking the neuroprotective effects of NGF, acting as selective activator of its receptors, both TrkA and p75NTR, thus promoting survival of various neuronal cell types. Our present research aims at determining whether and which aspects of the AD-related pathology, BNN27 is able to alleviate, exploring the cellular and molecular AD components and link these changes with improvements in the cognitive performance of an animal AD model, the 5xFAD mice. Our results clearly indicate that BNN27 administration significantly reduced amyloid-β load in whole brain of the animals, enhanced adult hippocampal neurogenesis, restored cholinergic function and synaptogenesis, reducing inflammatory activation and leading to significant restoration of cognitive functions. BNN27 may represent a new lead multimodal molecule with neuroprotective, neurogenic and anti-neuroinflammatory actions for developing druggable anti-Alzheimeric agents. Proteomics data are available via ProteomeXchange with the identifier PXD044699.

Small molecule modulators are powerful tools for selectively probing and manipulating proteins in native biological systems. However, the development of versatile modulators that exhibit desired properties is hindered by the lack of a rapid and robust synthetic strategy. Here, we develop a facile and reliable one‐step methodology for the generation of multifunctional toolboxes encompassing a wide variety of chemical modulators with different desired features. These modulators bind irreversibly to the protein target via a selective warhead. Key elements are introduced onto the warhead in a single step using multi‐component reactions. To illustrate the power of this new technology, we synthesized a library of diverse modulators designed to explore a highly challenging and poorly understood protein, human 15‐lipoxygenase‐1. Modulators made include; activity‐based/photoaffinity probes, chemosensors, photocrosslinkers, as well as light‐controlled and high‐affinity inhibitors. The efficacy of our compounds was successfully established through the provision of on demand inhibition and labeling of our target protein in vitro, in cellulo and in vivo; thus, proving that this technology has promising potential for applications in many complex biological systems.

Background The Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) multimodal lifestyle intervention yielded cognitive and other health benefits in older adults at risk of cognitive decline. The two-year multinational randomized controlled LETHE trial evaluates the feasibility of a digitally supported, adapted FINGER intervention among at-risk older adults. Technology is used to complement in-person activities, streamline the intervention delivery, personalize recommendations, and collect digital biomarkers. Methods Trial includes older adults (60–77 years) with digital readiness/experience with smart devices and increased dementia risk but without substantial cognitive impairment. Participants are enrolled at four sites (Austria, Finland, Italy, Sweden). At baseline, participants were randomized 1:1 ratio to 1) intervention i.e., structured multimodal lifestyle program (including diet, exercise, cognitive training, vascular/metabolic risk management, social stimulation, sleep/stress management) where in-person activities led by professionals are supported with an Android mobile phone application developed by the consortium (the LETHE App); or 2) control i.e., self-guided program (regular health advice; simplified App with no personalized/interactive content). All participants wear smartwatches to gather passive data (e.g., physical activity, sleep). Primary outcomes are retention, adherence, and change in validated dementia risk scores. Secondary outcomes include changes in lifestyle, cognition, stress, sleep, health-related quality of life, and health literacy. Additional outcomes (exploratory) include e.g. participant experiences and dementia-related biomarkers (Alzheimer’s disease blood markers, neuroimaging). A sub-study explores the feasibility of novel interactive technology (audio glasses, social robot). Results Recruitment began in September 2022, and the last participant was randomized in June 2023. In total, 156 individuals were randomized (mean age 69 years, 65% women; balanced recruitment across the four sites). Vascular and lifestyle risk factors were common (e.g., 65% with hypertension, 69% with hypercholesterolemia, 39% physically inactive), indicating successful recruitment of a population with risk reduction potential. Trial will be completed by summer 2025. Retention until the first post-baseline visit at 6 months is high (n = 2 discontinued, retention 98.7%). Conclusion LETHE provides crucial information about the feasibility of technology and a digitally supported FINGER lifestyle program to promote brain health. Digital tools specifically designed for older adults could offer potential for large-scale, cost-effective prevention programs. Trial registration ClinicalTrials.gov (NCT05565170).

Gastroretentive drug delivery systems can improve adherence in patients with chronic diseases (CDs), but current options lack dose flexibility and involve complex fabrication methods. Inspired by the hygroscopic deformation observed in multilayered pine cone scales, wherein hydration of the outer active layer induces cone closure, a one‐step fabrication method of a personalized 4D‐printed water‐actuated four‐arm polypill is demonstrated in this study. The bilayer‐arm polypill self‐deploys upon ingestion to prolong gastric retention and sustain drug release. By inversing the orientation of the swellable active layer at the polypill arms compared to pine cone scales, a differential swelling strain develops generating bending force that enables polypill deployment to constrain passage through the pylorus. Finite‐element analysis is used to model spatial changes in polymer phase swelling to ensure adequate deployment within the timeframe of gastric emptying. In a stomach model, the polypill expanded to 30 mm over 2 h, exceeding the diameter of the stomach model's distal end. In an in vitro release screening, biocompatible polymer composites capable of providing up to 6 days of release for a three‐drug combination for tuberculosis–HIV coinfected patients are identified. The bioinspired 4D‐printed polypill can serve as drug delivery platform for a range of CDs.

In this work, we introduce the first pipeline that combines a refraction-aware structure from motion (SfM) method with a deep learning model specifically designed for airborne bathymetry. We accurately estimate the 3D positions of the submerged points by integrating refraction geometry within the SfM optimization problem. This way, no refraction correction as post-processing is required. Experiments with simulated data that approach real-world capturing conditions demonstrate that SfM with refraction correction is extremely accurate, with submillimeter errors. We integrate our refraction-aware SfM within a deep learning framework that also takes into account radiometrical information, developing a combined spectral and geometry-based approach, with further improvements in accuracy and robustness to different seafloor types, both textured and textureless. We conducted experiments with real-world data at two locations in the southern Mediterranean Sea, with varying seafloor types, which demonstrate the benefits of refraction correction for the deep learning framework. We made our refraction-aware SfM open source, providing researchers in airborne bathymetry with a practical tool to apply SfM in shallow water areas.

The performance of electrochemical energy storage (EES) devices is determined by the inherent characteristics of electrode materials such as anodes and cathodes. 2D materials are increasingly being studied for their...

Small molecule modulators are powerful tools for selectively probing and manipulating proteins in native biological systems. However, the development of versatile modulators that exhibit desired properties is hindered by the lack of a rapid and robust synthetic strategy. Here, we develop a facile and reliable one‐step methodology for the generation of multifunctional toolboxes encompassing a wide variety of chemical modulators with different desired features. These modulators bind irreversibly to the protein target via a selective warhead. Key elements are introduced onto the warhead in a single step using multi‐component reactions. To illustrate the power of this new technology, we synthesized a library of diverse modulators designed to explore a highly challenging and poorly understood protein, human 15‐lipoxygenase‐1. Modulators made include; activity‐based/photoaffinity probes, chemosensors, photocrosslinkers, as well as light‐controlled and high‐affinity inhibitors. The efficacy of our compounds was successfully established through the provision of on demand inhibition and labeling of our target protein in vitro, in cellulo and in vivo; thus, proving that this technology has promising potential for applications in many complex biological systems.

Nonhuman animal models continue to be indispensable in neuroscience research for the foreseeable future. In recent years, animal‐right activists have been increasing the pressure on politicians and policymakers to phase out animal research. To address this pressure, we should adapt our communication habits, to be more open and transparent about (our) animal research and most importantly to expand the methods we use to communicate about our research and increase the extend of this outreach. In this editorial, we discuss the why and how of animal research communication.

During the next decade we expect novel radio astronomy instruments to come online and start producing datasets of high volume and complexity at a rate that will be orders of magnitude above any existing radio telescope. This development necessitates the adoption of new data processing approaches that take advantage of latest-generation computing facilities and analysis algorithms. In this chapter, we consider associated challenges from the viewpoint of both software architecture and scientific data processing workflow. We advocate taking a co-design approach, whereby hardware and software are developed and validated in close coordination, to ensure that HPC-based workflows meet performance, cost, and reliability goals as necessitated by the overwhelming data flow expected by different observational experiments. We consider software stack development following on the principle of separation of concerns, and with reproducibility and performance portability as primary design goals, for systems built on top of heterogeneous hardware platforms. Finally, motivated by the particular case of the LOFAR radio interferometer, we present a study on how to exploit large-scale parallel architectures for efficiently solving the gridding processing step.

At the scale of radio astronomy experiments for the next generation facilities discussed in this book, the computing infrastructure plays a crucial role, in particular with respect to High Performance Computing (HPC) systems. This chapter discusses the most recent advances in this area. Firstly, we address a new type of computing facilities, based on combining both CPUs and accelerators as GPUs and FPGAs into heterogeneous HPC systems. Secondly, we introduce a new architecture for enabling a more dynamical use of such heterogeneous hardware resources. Thirdly, we take a deep dive in software containerisation, a key technology for effectively scaling complex codes and fully exploiting computing resources while greatly improving scientific reproducibility. Finally, we conclude by providing an overview on how some recent yet widely adopted cloud-native technologies, as last-generation container orchestrators, can converge together with HPC-specific ones towards higher-level, unified frameworks.

In the present work, the ultrafast nonlinear optical (NLO) response of some molybdenum disulfide (MoS2), fluorinated graphene (FG), and FG/MoS2 heterostructure thin films was studied using the Z-scan and optical Kerr effect techniques employing femtosecond laser pulses at different excitation wavelengths (i.e., 400, 570, 610, 660, 800, and 1200 nm). The experiments have shown that the NLO response of the MoS2 and MoS2/FG films was significantly enhanced when the films were excited with 400, 610, and 660 nm laser pulses due to resonance effects with the close-lying excitons in these nanostructures. For a better evaluation of the resonant enhancement of the NLO response, measurements were also carried out at off-resonant wavelengths, i.e., at 570, 800, and 1200 nm. The presence of excitons in the MoS2 and MoS2/FG films resulted in strong saturable absorption and self-defocusing, with exceptionally large values of third-order susceptibilities χ⁽³⁾ ranging from 10–12 to 10–13 esu. In addition, the NLO response of the MoS2/FG heterostructure was found to be stronger than that of the individual MoS2 and FG films, most probably attributed to interlayer carrier transfer. The determined NLO parameters of the studied nanostructures were found to be comparable to, and in some cases exceeded, those of other reported 2D materials known to exhibit a strong NLO response as well. These findings not only advance the fundamental understanding of the contributions of excitons on the NLO response/properties of transition metal dichalcogenide-based ultrathin films but also highlight the importance of excitons for tailoring their NLO response in view of various applications in advanced optoelectronics and photonic devices.

Bottom-up, data-driven, large-scale models provide a mechanistic understanding of neuronal functions. A new study in PLOS Biology builds a biologically realistic model of the rodent CA1 region that aims to become an accessible tool for the whole hippocampal community.

Introduction Polygenic Risk Scores (PRS) are an emerging tool for predicting an individual’s genetic risk to a complex trait. Several methods have been proposed to construct and calculate these scores. Here, we develop a biologically driven PRS using the UK BioBank cohort through validated protein interactions (PPI) and network construction for psoriasis, incorporating variants mapped to the interacting genes of 14 psoriasis susceptibility (PSORS) loci, as identified from previous genetic linkage studies. Methods We constructed the PPI network via the implementation of two major meta-databases of protein interactions, and identified variants mapped to the identified PSORS-interacting genes. We selected only European unrelated participants including individuals with psoriasis and randomly selected healthy controls using an at least 1:4 ratio to maximize statistical power. We next compared our PPI-PRS model to (i) clinical risk models and (ii) conventional PRS calculations through p-value thresholding. Results Our PPI-PRS model provides comparable results to both clinical risk models and conventional approaches, despite the incorporation of a limited number of variants which have not necessarily reached genome-wide significance (GWS). Exclusion of variants mapped to the HLA-C locus, an established risk locus for psoriasis resulted in highly similar associations compared to our primary model, indicating the contribution of the genetic variability mapped to non-GWS variants in PRS computations. Discussion Our findings support the implementation of biologically driven approaches in PRS calculations in psoriasis, highlighting their potential clinical utility in risk assessment and treatment management.

We show that Poincaré polarization singularities, spiraling like a tornado, can be generated by superimposing two orthogonally polarized, abruptly auto-focusing ring-Airy beams that carry orbital angular momentum (OAM). Seeded by phase vortices of the same helicity, which are adapted to the high-intensity rings of one of the superimposing beams, these polarization singularities follow trajectories that twist and shrink in an accelerating fashion along their propagation. Reaching angular acceleration that exceeds 120 rad/mm², these Poincaré tornados can find application in singular optics, wavefront shaping, polarization engineering, and imaging through complex media.

Reconfigurable intelligent surfaces (RIS) can actively manipulate the wave propagation within a space, even in unconventional ways, enabling software-defined wireless propagation. Enabling real-time RIS operation requires a codebook, that is, a set of pre-calculated states of the RIS constituent elements that yield any of the supported macroscopic RIS functionalities, such as anomalous steering, splitting, and wave absorption. The codebook compilation process occurs offline, and requires the time consuming optimization of either an EM simulator, or an automated RIS measurement system. The process is especially resource-demanding in the case of RIS designs with no known analytical performance model, such as metasurfaces in the general sense. This article studies the synergy between metaheuristic optimizers and the RIS codebook compilation process. Specifically, well-known and widely efficient metaheuristic optimizers are imbued with attributes of the RIS physics, yielding considerable gains in the codebook compilation time. This process leverages correlations between microscopic configurations and macroscopic RIS responses, geometric optics, and EM simulators. The evaluation outcomes indicate a significant potential in the design of high-performing and resource-effective metaheuristics for RIS.

Mosquitoes threaten over half of the world’s population through vectored diseases such as malaria, zika, yellow fever, dengue, and chikungunya. Mosquitoes have a highly developed olfactory system attuned to chemotaxis relating to host-seeking, mating, and oviposition behavior. In this study, we aimed to determine the spatial efficacy of 2 plant-based repellent blends (Blend3 and Blend4 that had previously been found to successfully repel Aedes, Anopheles and Culex mosquitoes in wind tunnel assays) in excluding Aedes aegypti from the window entry. A new cage system was developed for parallel “no-choice” and “choice” olfactometric assays. In the no-choice trial, Blends 3 and 4, as well as commercial products (N, N-diethyl-3-methylbenzamide, p-menthane-3,8-diol [PMD], 3-(N-n-butyl-N-acetyl)-amino-propionic acid ethyl ester, and 2-(2-hydroxyethyl)-1-methylpropylstyrene 1-piperidine carboxylate), were adsorbed into filter papers of different sizes and placed in a window created between 2 attached bug dorms. Then, the number of mosquitoes entering the window was counted through a 6-min period. In choice olfactometric assays, Blends 3, 4, and PMD were adsorbed into filter paper and the number of mosquitoes moving away from Blend 3 and PMD were compared. No-choice assays showed that Blend3 (P < 0.001) and Blend4 (P = 0.0012) were more repellent than the best commercial product PMD. Additionally, while Blend 4 was significantly more repellent than Blend 3 (P = 0.012) in the choice assay, overall, these 2 blends show promise as new repellents for the spatial exclusion of Aedes aegypti from window entry alone or as part of a “push-pull’’ strategy.

Extracellular vesicles (EVs) are small membranous vesicles secreted by cells into their surrounding extracellular environment. Similar to mammalian EVs, plant EVs have emerged as essential mediators of intercellular communication in plants that facilitate the transfer of biological material between cells. They also play essential roles in diverse physiological processes including stress responses, developmental regulation, and defense mechanisms against pathogens. In addition, plant EVs have demonstrated promising health benefits as well as potential therapeutic effects in mammalian health. Despite the plethora of potential applications using plant EVs, their isolation and characterization remains challenging. In contrast to mammalian EVs, which benefit from more standardized isolation protocols, methods for isolating plant EVs can vary depending on the starting material used, resulting in diverse levels of purity and composition. Additionally, the field suffers from the lack of plant EV markers. Nevertheless, three main EV subclasses have been described from leaf apoplasts: tetraspanin 8 positive (TET8), penetration‐1‐positive (PEN1), and EXPO vesicles derived from exocyst‐positive organelles (EXPO). Here, we present an optimized protocol for the isolation and enrichment of small EVs (sEVs; <200 nm) from the apoplastic fluid from Nicotiana benthamiana leaves by ultracentrifugation. We analyze the preparation through transmitted electron microscopy (TEM), nanoparticle tracking analysis (NTA), and western blotting. We believe this method will establish a basic protocol for the isolation of EVs from N. benthamiana leaves, and we discuss technical considerations to be evaluated by each researcher working towards improving their plant sEV preparations. © 2024 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol : Isolation and enrichment of small extracellular vesicles (sEVs) from the apoplastic fluid of Nicotiana benthamiana leaves