National Centre of Scientific Research "Demokritos"

Senescence is a cellular stress response causing a stable exit from the cell cycle. Limitation of cell proliferation is accompanied by a variety of characteristic changes, including cellular and nuclear morphological alterations, chromatin rearrangements, metabolic reprogramming, nuclear envelope rupture, and an immunomodulatory secretome, termed senescence-associated secreted phenotype (SASP). Senescence is a robust mechanism of tissue homeostasis, with crucial roles in eliminating dysfunctional and/or premalignant cells, and tissue repair. Activation of oncogenes triggers senescence, which in turn arrests DNA-damaged cells. This type of response, known as oncogene-induced senescence (OIS) is a powerful barrier to oncogenesis. However, in specific contexts, senescent cells support tumor progression, mainly via their secretome-mediated activities. The dynamic, context-dependent and ambivalent nature of senescence challenges the identification, characterization, and specific targeting of senescent cells for disease management. Importantly, senescence is highly intertwined with DNA damage response and repair (DDR/R) machinery that safeguards genome integrity. DNA damage events are frequently prevalent, while DDR/R signaling pathways are active during cellular senescence. In this regard, it can serve as an auxiliary indicator for senescent cells. In this chapter, we emphasize DDR/R as a shared hallmark of cancer and senescence. We provide a wieldy toolkit of experimental methods for monitoring DDR-related senescence markers, and we demonstrate the potential of using natural language processing to extract additional DDR/R biomarkers tailored to specific cancer types. Our methodologies can facilitate a comprehensive study of senescence in aging and cancer.

Selective targeting of senescent cells has been thus far considered a widespread preventive strategy, as well as a main or adjuvant therapy for age-associated diseases, fueling the research on the discovery of senotherapeutics (i.e., senolytic or senomorphic compounds). Given that until now no single senotherapeutic has been reported to exert a universal anti-senescence action due to the cell- /tissue-, and context-dependent specificity of such compounds, seeking novel selective senotherapeutics remains of great importance. In this chapter, a research strategy that could be followed to screen natural product collections for putative senotherapeutics with enhanced specificity and reduced toxicity is presented, from the extraction of the source material and the isolation and chemical characterization of the compounds of interest to their biological evaluation in vitro and in vivo.

The work herein reviews the scientific literature on Machine Learning approaches for financial risk assessment using financial reports. We identify two prominent use cases that constitute fundamental risk factors for a company, namely misstatement detection and financial distress prediction. We further categorize the related work along four dimensions that can help highlight the peculiarities and challenges of the domain. Specifically, we group the related work based on (a) the input features used by each method, (b) the sources providing the labels of the data, (c) the evaluation approaches used to confirm the validity of the methods, and (d) the machine learning methods themselves. This categorization facilitates a technical overview of risk detection methods, revealing common patterns, methodologies, significant challenges, and opportunities for further research in the field.

https://authors.elsevier.com/c/1kiYrB8cd459C

Due to the growing interest of International Atomic Energy Agency (IAEA) Member States in implementing targeted radionuclide therapy (TRT) in general, the demand for alpha -emitting radionuclides and radiopharmaceuticals is enormous. As an international platform for peaceful applications of radionuclides, the IAEA has been implementing several activities focusing on the production and quality control of alpha emitters and radiopharmaceuticals as well as capacity building in the field, through Technical Meetings, Workshops, Publications and Conference Supports, IAEA -Technical Cooperation Projects (CRP) and Technical Cooperation Program (TC). This review article summarises the IAEA activities on the production and quality control of alpha emitter radiopharmaceuticals for targeted alpha therapy (TAT) and a roadmap to future steps including but not limited to the ongoing CRP on 225Ac - radiopharmaceuticals.

Complex diseases pose challenges in prediction due to their multifactorial and polygenic nature. This study employed machine learning (ML) to analyze genomic data from the UK Biobank, aiming to predict the genomic predisposition to complex diseases like multiple sclerosis (MS) and Alzheimer’s disease (AD). We tested logistic regression (LR), ensemble tree methods, and deep learning models for this purpose. LR displayed remarkable stability across various subsets of data, outshining deep learning approaches, which showed greater variability in performance. Additionally, ML methods demonstrated an ability to maintain optimal performance despite correlated genomic features due to linkage disequilibrium. When comparing the performance of polygenic risk score (PRS) with ML methods, PRS consistently performed at an average level. By employing explainability tools in the ML models of MS, we found that the results confirmed the polygenicity of this disease. The highest-prioritized genomic variants in MS were identified as expression or splicing quantitative trait loci located in non-coding regions within or near genes associated with the immune response, with a prevalence of human leukocyte antigen (HLA) gene annotations. Our findings shed light on both the potential and the challenges of employing ML to capture complex genomic patterns, paving the way for improved predictive models.

CDs/TiO2 nanohybrids were synthesized and tested for photocatalytic H2 production from aqueous media through simulated solar light-driven photocatalytic reactions. Firstly, three different types of CDs were prepared through green methods, specifically hydrothermal treatment and microwave irradiation, using citric acid and urea as precursors in varying molar ratios. After a multi-step purification procedure, impurity-free CDs were obtained. The as-synthesized CDs were thoroughly characterized using UV-Vis, FT-IR, and PL spectroscopy, along with HR-TEM. The results revealed that the size and optical and physicochemical properties of CDs can be tailored by selecting the precursors’ ratio and the synthetic approach. The heterostructured CDs/TiO2 photocatalysts were formed solvothermally and were analyzed using UV-Vis/DRS, FT-IR, and XPS techniques, which confirmed the effective incorporation of CDs and the improved properties of TiO2. The use of sacrificial reagents is among the most common strategies for enhancing H2 production from water through photocatalytic processes; herein, ethanol was selected as a green liquid organic hydrogen carrier. A maximum H2 production rate of 0.906 μmol H2/min was achieved, while the recyclability study demonstrated that the photocatalyst maintained stable performance during multiple cycles of reuse. Thus, optimizing the synthesis conditions of CDs/TiO2 nanohybrids resulted in the creation of environmentally friendly and reusable photocatalysts.

Neutrons, owing to their unique properties, serve as indispensable probes for investigating the structure and dynamics of materials across various length scales. The scientific community utilizing neutron research infrastructures encompasses a diverse range of disciplines, making it challenging to quantify its scientific and societal impact. To address this challenge, we apply Natural Language Processing (NLP) and machine learning techniques to analyze the scientific output of the European neutron science community. Leveraging open-source software toolkits, our method allows for the quantitative assessment of community evolution and research focus. Our analysis reveals consistent growth in the neutron community despite a reduction in sources, underscoring the enduring significance of neutron methods in scientific research. Furthermore, an increase in unique authors and an even distribution of publications across diverse scientific topics highlight the community’s interdisciplinary nature and collaborative spirit. While this study emphasizes neutron scattering, our methodology holds promise for a broad range of scientific communities reliant on Large Research Infrastructures (LRIs), offering opportunities for collaboration, optimization of experimental approaches, and informed decision-making by governmental and funding bodies.

In previous RENEB interlaboratory comparisons based on the manual scoring of dicentric chromosomes, a tendency for systematic overestimation for doses > 2.5 Gy was found. However, these exercises included only very few doses in the high dose range, and they were heterogeneous in terms of radiation quality and evaluation mode, and comparable only to a limited extent. Here, this presumed deviation was explored by investigating three doses > 2.5 Gy. Blood samples were irradiated (2.56, 3.41 and 4.54 Gy) using a ⁶⁰Co source and sent to 14 member laboratories of the RENEB network, which performed the dicentric chromosome assay (manual and/or semi-automatic scoring) and reported dose estimates. Most participants provided estimates that agreed very well with the physical reference doses and all provided dose estimates were in the correct clinical category (> 2 Gy). The previously observed tendency for a systematic bias across all laboratories was not confirmed. However, tendencies for systematic underestimation were detected for dose estimations for reference doses given in terms of absorbed dose to blood and for some participants, a laboratory-specific trend of systematic under- or overestimation was observed. The importance of regularly performed quality checks for a broad dose range became obvious to avoid misinterpretation of results.

In this study, composites of hydroxyl-terminated polydimethylsiloxane (PDMS) reinforced with multiwall carbon nanotubes (MWCNTs) were prepared using solution mixing assisted by sonication. The vulcanization behavior of PDMS was investigated using modulated temperature DSC, revealing a decrease in the reaction rate at higher MWCNT loadings. The prepared nanocomposites were characterized for their thermomechanical and dielectric properties, as well as for oxygen permeability and electromagnetic interference shielding effectiveness (EMI SE). Thermogravimetric Analysis (TGA) showed that thermal degradation of the specimens began at lower temperatures and ended at higher temperatures compared to pure PDMS. Enhancements in tensile strength and Young’s modulus were also recorded, particularly at higher filler concentrations. Swelling after immersion in toluene was lower for all MWCNT/PDMS composites compared to pure PDMS. Notably, membranes made from MWCNT/PDMS composites demonstrated a significant decrease in O 2 permeability. Dielectric Relaxation Spectroscopy (DRS) revealed that the percolation threshold was reached at a low CNT content of 0.036 phr. The Electromagnetic interference (EMI) Shielding Effectiveness (SE) of the prepared MWCNT/PDMS membranes -recorded in the X-band- was strongly dependent on the CNTs loading. Membranes with thickness of ∼1.1 mm exhibited SE values of 5 and 17 dB, for loadings of 0.5 and 4.0 phr, respectively. Based on these results, it is concluded that MWCNTs/PDMS composites prepared via solution mixing demonstrate improvement in their performance in many critical properties, even at very low reinforcement levels.

We report the discovery of a Nurr1-RXRα heterodimer-selective rexinoid which emerged from the structural modification of aminopyrimidine XCT0135908. Although XCT0135908 demonstrated high selectivity for the Nurr1-RXRα heterodimer over other RXRα dimerization partners, its poor in vivo stability and limited brain penetration hindered its utility. Structure–activity relationship (SAR) studies alongside bioactivity evaluations of a diverse series of substituted pyrimidines led to BRF110, a brain-penetrant compound retaining the selective activation of the Nurr1-RXRα heterodimer. BRF110, as XCT0135908, protects dopaminergic cells against the Parkinson’s disease-related toxin MPP+ and increases BDNF transcription in mice. Notably, BRF110, in contrast to the market-approved pan-RXR agonist bexarotene, did not elevate triglyceride levels, indicating that enhanced heterodimer selectivity can mitigate off-target in vivo side effects of rexinoids. These findings highlight the potential of heterodimer-selective scaffolds as a strategy for improving the therapeutic profile of rexinoids, addressing significant challenges in the clinical development of RXR-targeting molecules.

Rare, germline loss-of-function variants in a handful of DNA repair genes are associated with epithelial ovarian cancer. The aim of this study was to evaluate the role of rare, coding, loss-of-function variants across the genome in epithelial ovarian cancer. We carried out a gene-by-gene burden test with various histotypes using data from 2573 non-mucinous cases and 13,923 controls. Twelve genes were associated at a False Discovery Rate of less than 0.1 of which seven were the known ovarian cancer susceptibility genes BRCA1 , BRCA2 , BRIP1 , RAD51C , RAD51D, MSH6 and PALB2 . The other five genes were OR2T35, HELB, MYO1A and GABRP which were associated with non-high-grade serous ovarian cancer and MIGA1 which was associated with high-grade serous ovarian cancer. Further support for the association of HELB association comes from the observation that loss-of-function variants in HELB are associated with age at natural menopause and Mendelian randomisation analysis shows an association between genetically predicted age at natural menopause and endometrioid ovarian cancer, but not high-grade serous ovarian cancer.

Background: Cancer cells are avid extracellular vesicle (EV) producers. EVs transport transforming growth factor-β (TGF-β), which is commonly activated under late stages of cancer progression. Nevertheless, whether TGF-β signaling coordinates EV biogenesis is a relevant topic that remains minimally explored. Method: We sought after specific TGF-β pathway mediators that could regulate EV release. To this end, we used a large number of cancer cell models, coupled to EV cell biological assays, unbiased proteomic and transcriptomic screens, followed by signaling and cancer biology analyses, including drug resistance assays. Results: We report that TGF-β, by activating its type I receptor and MEK-ERK1/2 signaling, increased the numbers of EVs released by human cancer cells. Upon examining cholesterol as a mediator of EV biogenesis, we delineated a pathway whereby ERK1/2 acted by phosphorylating sterol regulatory element-binding protein-2 that transcriptionally induced 7-dehydrocholesterol reductase expression, thus raising cholesterol abundance at both cellular and EV levels. Notably, inhibition of MEK or cholesterol synthesis, which impaired TGF-β-induced EV secretion, sensitized cancer cells to chemotherapeutic drugs. Furthermore, proteomic profiling of two distinct EV populations revealed that EVs secreted by TGF-β-stimulated cells were either depleted or enriched for different sets of cargo proteins. Among these, latent-TGF-β1 present in the EVs was not affected by TGF-β signaling, while TGF-β pathway-related molecules (e.g., matrix metalloproteinases, including MMP9) were either uniquely enriched on EVs or strongly enhanced after TGF-β stimulation. EV-associated latent-TGF-β1 activated SMAD signaling, even when EV uptake was blocked by heparin, indicating competent signaling capacity from target cell surface receptors. MMP inhibitor or proteinase treatment blocked EV-mediated SMAD signaling, suggesting that EVs require MMP activity to release the active TGF-β from its latent complex, a function also linked to the EV-mediated transfer of pro-migratory potential and ability of cancer cells to survive in the presence of cytotoxic drugs. Conclusion: Hence, we delineated a novel signaling cascade that leads to high rates of EV generation by cancer cells in response to TGF-β, with cholesterol being a key intermediate step in this mechanism.

Pathogenic infections of silkworms constitute the greatest threat to sericulture. An attractive approach to the improvement in silkworm health and performance comprises the use of probiotics, i.e., microorganisms that confer beneficial properties such as an increased growth rate and resistance against pathogens. While this method has already resulted in promising results, generally, there is a lack of a rational basis for guidance on the selection of probiotics. This review attempts to organize useful information that needs to be considered for the successful application of probiotics: the constitution of the microbiota in silkworms and its origins; the interaction of the major silkworm pathogens with the microbiota; and the microorganisms that have been used so far as silkworm probiotics. Our analysis points to two major issues that seem of vital importance: (1) the absence of a “core microbiota” in silkworms which necessitates continuous supply of beneficial microorganisms according to environmental conditions and (2) the apparent negative impact that some other microorganisms can have on resistance against baculovirus infections. Recent findings have reported the beneficial effects of lactic acid bacteria (Lactobacillus sp.) when applied as probiotics in improving silkworm health and performance.

Lanthanides have seen rapid growth in the pharmaceutical and biomedical field, thus necessitating the development of hybrid metal–organic materials capable of exerting defined biological activities. Ternary hybrid lanthanide compounds were synthesized through reaction systems of Ln(III) (Ln = La, Nd, Eu) involving the antioxidant flavonoid chrysin (Chr) and 1,10-phenanhtroline (phen) under solvothermal conditions, thus leading to pure crystalline materials. The so-derived compounds were characterized physicochemically in the solid state through analytical (elemental analysis), spectroscopic (FT-IR, UV-visible, luminescence, ESI-MS, circular dichroism, 151Eu Mössbauer), magnetic susceptibility, and X-ray crystallographic techniques. The analytical and spectroscopic data corroborate the 3D structure of the mononuclear complex assemblies and are in line with theoretical calculations (Bond Valence Sum and Hirshfeld analysis), with their luminescence suggesting quenching on the flavonoid-phen electronic signature. Magnetic susceptibility data suggest potential correlations, which could be envisioned, supporting future functional sensors. At the biological level, the title compounds were investigated for their (a) ability to interact with bovine serum albumin and (b) antibacterial efficacy against Gram(−) (E. coli) and Gram(+) (S. aureus) bacteria, collectively revealing distinctly configured biological profiles and suggesting analogous applications in cellular (patho)physiologies.

The photophysical properties of five dyes, i.e., perylene, anthracene, aminoanthracene, 1,6-diphenylhexatriene, and 7-diethylamino-4-methylcoumarin, in solvent and attached to the poly(methyl methacrylate) (PMMA) polymer, were studied via DFT and TD-DFT calculations. Their absorption and emission spectra were calculated, while for the PMMA-dye systems, their absorption spectra were measured experimentally, in good agreement with the calculated ones. In the PMMA-dye systems, charge transfer from the dye to PMMA was observed, and in the case of perylene, electron transfer from its ground state was also observed. It was found that the PMMA-dye systems can interact photochemically via laser illumination, and provided that the charge transfer will be enhanced by using the appropriate laser parameters, the systems may be candidates for the design of materials for specific nanopatterning needs.

Graphene is a material, which has attracted great attention of the scientific community in several fields of biomedicine, neurosciences being one of the fields holding great interest for the application of graphene-based materials and devices. Our study aimed to determine the in vivo brain tissue reaction and to study the possible impairment of memory in a long-term Graphene exposure. Towards this aim we tested the toxicity of graphene membrane in the form of few layers (few layers graphene, FLG) implanted on the frontal brain cortex of adult Wistar rats after careful durotomy. The results from this study advance our knowledge on graphene in vivo toxicity in CNS and suggest that the application of FLG as a patch on the brain cortex seems to be quite safe under the experimental conditions tested, herein as no change in locomotor activity of the rats or major histopathological reactions of the brain to the material were observed.