Human colorectal cancer: upregulation of the adaptor protein Rai in TILs leads to cell dysfunction by sustaining GSK-3 activation and PD-1 expression

Background: The immunosuppressive tumor microenvironment (TME) of colorectal cancer (CRC) is a major hurdle for immune checkpoint inhibitor-based therapies. Hence characterization of the signaling pathways driving T cell exhaustion within TME is a critical need for the discovery of novel therapeutic targets and the development of effective therapies. We previously showed that (i) the adaptor protein Rai is a negative regulator of T cell receptor signaling and T helper 1 (Th1)/Th17 cell differentiation; and (ii) Rai deficiency is implicated in the hyperactive phenotype of T cells in autoimmune diseases. Methods: The expression level of Rai was measured by qRT-PCR in paired peripheral blood T cells and T cells infiltrating tumor tissue and the normal adjacent tissue in CRC patients. The impact of hypoxia-inducible factor (HIF)-1α on Rai expression was evaluated in T cells exposed to hypoxia and by performing chromatin immunoprecipitation assays and RNA interference assays. The mechanism by which upregulation of Rai in T cells promotes T cell exhaustion were evaluated by flow cytometric, qRT-PCR and western blot analyses. Results: We show that Rai is a novel HIF-1α-responsive gene that is upregulated in tumor infiltrating lymphocytes of CRC patients compared to patient-matched circulating T cells. Rai upregulation in T cells promoted Programmed cell Death protein (PD)-1 expression and impaired antigen-dependent degranulation of CD8+ T cells by inhibiting phospho-inactivation of glycogen synthase kinase (GSK)-3, a central regulator of PD-1 expression and T cell-mediated anti-tumor immunity. Conclusions: Our data identify Rai as a hitherto unknown regulator of the TME-induced exhausted phenotype of human T cells

Theoretical Properties of Graph Neural Networks

Graph Neural Networks (GNNs) have emerged in recent years as a powerful tool to learn tasks across a wide range of graph domains in a data-driven fashion; based on a message passing mechanism, GNNs have gained increasing popularity due to their intuitive formulation, closely linked with the Weisfeiler-Lehman (WL) test for graph isomorphism, to which they have proven equivalent. In this thesis, we provide a broad overview of two essential properties of GNNs by a theoretical point of view, namely, their approximation power and their generalization capabilities. We show that modern GNNs are universal approximators, given that they are made by a sufficient number of layers, which is tightly linked to the stable node coloring of the 1-WL test. GNNs are shown to be universal approximators also on more complex graph domains, like edge-attributed graphs and dynamic graphs. Generalization capabilities of GNNs are investigated by different perspectives. Bounds on the VC dimension of GNNs are provided with respect to the usual hyperparameters and with respect to the number of colors derived from the 1-WL test. GNNs ability to generalize to unseen data is also explored by a neurocognitive point of view, determining whether these models are able to learn the so-called identity effects

Information and communication technology and labour productivity growth: a production‐frontier approach

This work provides evidence of the positive impact of Information and Communication Technology (ICT) on the labour productivity growth of 24 countries, members of the OECD, from 1995 to 2019. Using a non-parametric production-frontier approach, we decompose labour productivity growth into components attributable to technological change (shifts in the world production frontier), efficiency change (movements toward or away from the frontier), physical (non-ICT) capital change and ICT capital change (movements along the frontier). We find that, on average, the most significant improvement in worldwide labour productivity is attributable to technological change, non-ICT, and ICT capital change over 1995-2019. In addition, we confirm the role of ICT as a general-purpose technology that needs to implement complementary changes in business organisations to exploit its growth opportunities fully. Finally, we conclude that ICT capital contributes to convergence

An Innovative Solution for Efficient Workflow Management in Healthcare

Hospitals are challenged to provide a wider range of services due to a growing patient population, leading to a faster deterioration rate compared to other buildings. Recent years have seen a focus on improving maintenance management in hospitals through strategies, performance measurements, and Information Technology. Challenges include resource allocation, communication gaps, and workflow monitoring. Healthcare workflow management involves various stakeholders and aims to ensure safe, efficient, and effective patient care while minimizing waste and reducing costs. Workflow Management Systems (WFMSs) are promising solutions, automating administrative procedures to enhance efficiency and effectiveness in healthcare services. The paper presents a RESTful WFMS developed in Microsoft .NET 6, utilizing the open-source .NET library Elsa Workflows. It introduces pre-typed sub-workflows, each defined in JSON format, allowing users to customize workflows using Graphic User Interfaces (GUIs). The system stores information in a Microsoft SQL Server database and interacts with the hospital Computer Aided Facility Management (CAFM) system via APIs. The platform enables managers and department heads to create customizable workflows in a no-code environment. The system is used in an actual healthcare environment at the “Le Scotte” University Hospital in Siena, Italy

A novel method to estimate the response of habitat types to nitrogen deposition

Increasing nitrogen depositions adversely affect European landscapes, including habitats within the Natura2000 network. Critical loads for nitrogen deposition have been established to quantify the loss of habitat quality. When the nitrogen deposition rises above a habitat-specific critical load, the quality of the focal habitat is expected to be negatively influenced. Here, we investigate how the quality of habitat types is affected beyond the critical load. We calculated response curves for 60 terrestrial habitat types in the Netherlands to the estimated nitrogen deposition (EMEP-data). The curves for habitat types are based on the occurrence of their characteristic plant species in North-Western Europe (plot data from the European Vegetation Archive). The estimated response curves were corrected for soil type, mean annual temperature and annual precipitation. Evaluation was carried out by expert judgement, and by comparison with gradient deposition field studies. For 39 habitats the response to nitrogen deposition was judged to be reliable by five experts, while out of the 41 habitat types for which field studies were available, 25 showed a good agreement. Some of the curves showed a steep decline in quality and some a more gradual decline with increasing nitrogen deposition. We compared the response curves with both the empirical and modelled critical loads. For 41 curves, we found a decline already starting below the critical load

The role of ethnicity and native-country income in multiple sclerosis: the Italian multicentre study (MS-MigIT)

Objective: Multiple sclerosis (MS) is a complex disorder in which environmental and genetic factors interact modifying disease risk and course. This multicentre, case-control study involving 18 Italian MS Centres investigated MS course by ethnicity and native-country economic status in foreign-born patients living in Italy. Methods: We identified 457 MS patients who migrated to Italy and 893 age- and sex-matched native-born Italian patients. In our population, 1225 (93.2%) subjects were White Europeans and White Northern Americans (WENA) and 89 (6.8%) patients were from other ethnical groups (OEG); 1109 (82.1%) patients were born in a high-income (HI) Country and 241 (17.9%) in a low-middle-income (LMI) Country. Medical records and patients interviews were used to collect demographic and disease data. Results: We included 1350 individuals (973 women and 377 men); mean (SD) age was 45.0 (11.7) years. At onset, 25.45% OEG patients vs 12.47% WENA (p = 0.039) had > 3 STIR spine lesions. At recruitment, the same group featured mean (SD) EDSS score of 2.85 (2.23) vs 2.64 (2.28) (p = 0.044) reached in 8.9 (9.0) vs 12.0 (9.0) years (p = 0.018) and underwent 1.10 (4.44) vs. 0.99 (0.40) annual MRI examinations (p = 0.035). At disease onset, patients from LMI countries had higher EDSS score than HI patients (2.40 (1.43) vs 1.99 (1.17); p = 0.032). Discussion: Our results suggested that both ethnicity and socio-economic status of native country shape MS presentation and course and should be considered for an appropriate management of patients. To the best of our knowledge, this is the first study reporting on the impact of ethnicity in MS at an individual level and beyond an ecological population-perspective

Exposure to nanoplastics and nanomaterials either single and combined affects the gill-associated microbiome of the Antarctic soft-shelled clam Laternula elliptica

Nanoplastics and engineering nanomaterials (ENMs) are contaminants of emerging concern (CECs), increasingly being detected in the marine environment and recognized as a potential threat for marine biota at the global level including in polar areas. Few studies have assessed the impact of these anthropogenic nanoparticles in the microbiome of marine invertebrates, however combined exposure resembling natural scenarios has been overlooked. The present study aimed to evaluate the single and combined effects of polystyrene nanoparticles (PS NP) as proxy for nanoplastics and nanoscale titanium dioxide (nano-TiO2) on the prokaryotic communities associated with the gill tissue of the Antarctic soft-shell clam Laternula elliptica, a keystone species of marine benthos Wild-caught specimens were exposed to two environmentally relevant concentrations of carboxylated PS NP (PS-COOH NP, ∼62 nm size) and nano-TiO2 (Aeroxide P25, ∼25 nm) as 5 and 50 μg/L either single and combined for 96h in a semi-static condition.Our findings show a shift in microbiome composition in gills of soft-shell clams exposed to PS NP and nano-TiO2 either alone and in combination with a decrease in the relative abundance of OTU1 (Spirochaetaceae). In addition, an increase of gammaproteobacterial OTUs affiliated to MBAE14 and Methylophagaceae (involved in ammonia denitrification and associated with low-quality water), and the OTU Colwellia rossensis (previously recorded in polluted waters) was observed. Our results suggest that nanoplastics and nano-TiO2 alone and in combination induce alterations in microbiome composition by promoting the increase of negative taxa over beneficial ones in the gills of the Antarctic soft-shell clam. An increase of two low abundance OTUs in PS-COOH NPs exposed clams was also observed. A predicted gene function analysis revealed that sugar, lipid, protein and DNA metabolism were the main functions affected by either PS-COOH NP and nano-TiO2 exposure. The molecular functions involved in the altered affiliated OTUs are novel for nano-CEC exposures

An Efficient Ray-Based Modeling Approach for Scattering from Reconfigurable Intelligent Surfaces

Reconfigurable Intelligent Surfaces (RISs), which can be implemented using metasurface technology or reflect/ transmit antenna array technology, have garnered significant attention in research studies focused on both their technological aspects and potential applications. While various modeling approaches have been proposed - ranging from electromagnetic simulations and analytical integral formulations to simplified approaches based on scattering matrix theory - there remains a great need for efficient and electromagnetically-consistent macroscopic models that can accurately simulate scattering from RISs, particularly for realistic simulations of RIS-based wireless networks. Building on previous work based on the characterization of the RIS through a surface impedance (or spatial modulation) function and a few parameters, in the present paper we propose a fully ray-based approach for the computation of the re-radiated field that can be easily embedded in efficient, forward ray tracing (also known as ray launching) models. We validate the proposed model by comparison to well established methods available in the literature. Results show that, although the considered method is based on a completely different formulation and is much more efficient than integral formulation methods, results are almost indistinguishable in some benchmark cases