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IntroductionEosinophilic esophagitis (EoE) is a chronic, immune-mediated inflammation of the esophagus, characterized by symptoms related to esophageal dysfunction, resulting from severe eosinophilic infiltration of the esophageal mucosa. It is common in atopic subjects and food antigens have been identified as the most common triggers. However, a seasonal variation in EoE prevalence, correlated with air pollen levels, is reported, suggesting that also aeroallergens may play a role. Little is known about the interplay between EoE and concomitant atopy treatment for aeroallergens.Case presentationWe describe the case of an 11-year-old boy who presented dysphagia, vomiting, drooling, and chest pain while eating meat, developed 15 months after receiving sublingual immunotherapy (SLIT) for Alternaria (SUBLIVAC®). He underwent esophagogastroduodenoscopy (EGD) revealing severe eosinophilic predominant inflammation (100 eos/HPF), consistent with the diagnosis of EoE, not improving at the EGDs performed after both omeprazole and topical corticosteroids treatment, despite symptom improvement. Afterward, immunotherapy was switched from sublingual to injective form. At the EGD performed 1 month later, macroscopic examination of the esophageal mucosa was normal and eosinophilic infiltration was significantly decreased (5–10 eos/HPF).ConclusionsSLIT may induce EoE by chronic antigenic exposure of oral mucosa in patients with a robust allergic susceptibility: while attenuating the IgE-mediated immune reactions, the progressive contact with the causative allergen might induce a chronic stimulation of the immune system with the consequent activation of tissue eosinophils. Our data suggest monitoring patients receiving SLIT for EoE symptoms and to discontinue SLIT on their earlier appearance, possibly as a first-line treatment.

Type 1 diabetes (T1D) presents a persistent medical challenge, demanding innovative strategies for sustained glycemic control and enhanced patient well-being. Beta cells are specialized cells in the pancreas that produce insulin, a hormone that regulates blood sugar levels. When beta cells are damaged or destroyed, insulin production decreases, which leads to T1D. Allo Beta Cell Transplantation has emerged as a promising therapeutic avenue, with the goal of reinstating glucose regulation and insulin production in T1D patients. However, the path to success in this approach is fraught with complex immunological hurdles that demand rigorous exploration and resolution for enduring therapeutic efficacy. This exploration focuses on the distinct immunological characteristics inherent to Allo Beta Cell Transplantation. An understanding of these unique challenges is pivotal for the development of effective therapeutic interventions. The critical role of glucose regulation and insulin in immune activation is emphasized, with an emphasis on the intricate interplay between beta cells and immune cells. The transplantation site, particularly the liver, is examined in depth, highlighting its relevance in the context of complex immunological issues. Scrutiny extends to recipient and donor matching, including the utilization of multiple islet donors, while also considering the potential risk of autoimmune recurrence. Moreover, unanswered questions and persistent gaps in knowledge within the field are identified. These include the absence of robust evidence supporting immunosuppression treatments, the need for reliable methods to assess rejection and treatment protocols, the lack of validated biomarkers for monitoring beta cell loss, and the imperative need for improved beta cell imaging techniques. In addition, attention is drawn to emerging directions and transformative strategies in the field. This encompasses alternative immunosuppressive regimens and calcineurin-free immunoprotocols, as well as a reevaluation of induction therapy and recipient preconditioning methods. Innovative approaches targeting autoimmune recurrence, such as CAR Tregs and TCR Tregs, are explored, along with the potential of stem stealth cells, tissue engineering, and encapsulation to overcome the risk of graft rejection. In summary, this review provides a comprehensive overview of the inherent immunological obstacles associated with Allo Beta Cell Transplantation. It offers valuable insights into emerging strategies and directions that hold great promise for advancing the field and ultimately improving outcomes for individuals living with diabetes.

BackgroundThe World Health Organization’s strategy toward healthy aging fosters person-centered integrated care sustained by eHealth systems. However, there is a need for standardized frameworks or platforms accommodating and interconnecting multiple of these systems while ensuring secure, relevant, fair, trust-based data sharing and use. The H2020 project GATEKEEPER aims to implement and test an open-source, European, standard-based, interoperable, and secure framework serving broad populations of aging citizens with heterogeneous health needs. ObjectiveWe aim to describe the rationale for the selection of an optimal group of settings for the multinational large-scale piloting of the GATEKEEPER platform. MethodsThe selection of implementation sites and reference use cases (RUCs) was based on the adoption of a double stratification pyramid reflecting the overall health of target populations and the intensity of proposed interventions; the identification of a principles guiding implementation site selection; and the elaboration of guidelines for RUC selection, ensuring clinical relevance and scientific excellence while covering the whole spectrum of citizen complexities and intervention intensities. ResultsSeven European countries were selected, covering Europe’s geographical and socioeconomic heterogeneity: Cyprus, Germany, Greece, Italy, Poland, Spain, and the United Kingdom. These were complemented by the following 3 Asian pilots: Hong Kong, Singapore, and Taiwan. Implementation sites consisted of local ecosystems, including health care organizations and partners from industry, civil society, academia, and government, prioritizing the highly rated European Innovation Partnership on Active and Healthy Aging reference sites. RUCs covered the whole spectrum of chronic diseases, citizen complexities, and intervention intensities while privileging clinical relevance and scientific rigor. These included lifestyle-related early detection and interventions, using artificial intelligence–based digital coaches to promote healthy lifestyle and delay the onset or worsening of chronic diseases in healthy citizens; chronic obstructive pulmonary disease and heart failure decompensations management, proposing integrated care management based on advanced wearable monitoring and machine learning (ML) to predict decompensations; management of glycemic status in diabetes mellitus, based on beat to beat monitoring and short-term ML-based prediction of glycemic dynamics; treatment decision support systems for Parkinson disease, continuously monitoring motor and nonmotor complications to trigger enhanced treatment strategies; primary and secondary stroke prevention, using a coaching app and educational simulations with virtual and augmented reality; management of multimorbid older patients or patients with cancer, exploring novel chronic care models based on digital coaching, and advanced monitoring and ML; high blood pressure management, with ML-based predictions based on different intensities of monitoring through self-managed apps; and COVID-19 management, with integrated management tools limiting physical contact among actors. ConclusionsThis paper provides a methodology for selecting adequate settings for the large-scale piloting of eHealth frameworks and exemplifies with the decisions taken in GATEKEEPER the current views of the WHO and European Commission while moving forward toward a European Data Space.

Patients surviving head and neck cancer (HNC) suffer from high physical, psychological, and socioeconomic burdens. Achieving cancer-free survival with an optimal quality of life (QoL) is the primary goal for HNC patient management. So, maintaining lifelong surveillance is critical. An ambitious goal would be to carry this out through the advanced analysis of environmental, emotional, and behavioral data unobtrusively collected from mobile devices. The aim of this clinical trial is to reduce, with non-invasive tools (i.e., patients’ mobile devices), the proportion of HNC survivors (i.e., having completed their curative treatment from 3 months to 10 years) experiencing a clinically relevant reduction in QoL during follow-up. The Big Data for Quality of Life (BD4QoL) study is an international, multicenter, randomized (2:1), open-label trial. The primary endpoint is a clinically relevant global health-related EORTC QLQ-C30 QoL deterioration (decrease ≥10 points) at any point during 24 months post-treatment follow-up. The target sample size is 420 patients. Patients will be randomized to be followed up using the BD4QoL platform or per standard clinical practice. The BD4QoL platform includes a set of services to allow patients monitoring and empowerment through two main tools: a mobile application installed on participants’ smartphones, that includes a chatbot for e-coaching, and the Point of Care dashboard, to let the investigators manage patients data. In both arms, participants will be asked to complete QoL questionnaires at study entry and once every 6 months, and will undergo post-treatment follow up as per clinical practice. Patients randomized to the intervention arm (n=280) will receive access to the BD4QoL platform, those in the control arm (n=140) will not. Eligibility criteria include completing curative treatments for non-metastatic HNC and the use of an Android-based smartphone. Patients undergoing active treatments or with synchronous cancers are excluded.Clinical Trial Registration: ClinicalTrials.gov, identifier (NCT05315570).

We introduce the first IJMS World Conference of Medical Student Research as a unique opportunity for medical students and early-career scientists around the globe to share the results of their research in an online worldwide platform, aimed at increasing accessibility to research for medical students and creating bonds of collaborations between participants and future scientists and leaders of medical research education. This is also the second issue of the 10-year anniversary of the Journal, and we describe in summary the published research and experiences of this issue.

The European Alps stretch over a range of climate zones which affect the spatial distribution of snow. Previous analyses of station observations of snow were confined to regional analyses. Here, we present an Alpine-wide analysis of snow depth from six Alpine countries – Austria, France, Germany, Italy, Slovenia, and Switzerland – including altogether more than 2000 stations of which more than 800 were used for the trend assessment. Using a principal component analysis and k-means clustering, we identified five main modes of variability and five regions which match the climatic forcing zones: north and high Alpine, north-east, north-west, south-east, and south and high Alpine. Linear trends of monthly mean snow depth between 1971 and 2019 showed decreases in snow depth for most stations from November to May. The average trend among all stations for seasonal (November to May) mean snow depth was −8.4 % per decade, for seasonal maximum snow depth −5.6 % per decade, and for seasonal snow cover duration −5.6 % per decade. Stronger and more significant trends were observed for periods and elevations where the transition from snow to snow-free occurs, which is consistent with an enhanced albedo feedback. Additionally, regional trends differed substantially at the same elevation, which challenges the notion of generalizing results from one region to another or to the whole Alps. This study presents an analysis of station snow depth series with the most comprehensive spatial coverage in the European Alps to date.

The aim of the paper is to describe the spread forest fire event occurred in the Italian Alps in 2017 under extremely drought conditions. In the study the root causes of wildfires and their direct relapses to the air quality of the Western Po valley and the urban centre of Torino have been assessed by means of air pollution measurements (focused to particulate matter with reference samplers and optical particle counters OPCs), meteorological indicators and additional public data. Results show a good correlation among different urban sites and instrument technologies. Concentration data, compared with environmental conditions and historical values describe the clear impact of fires on both local and regional air quality. Indeed, the deferred impact of wildfires on the local wood biomass energy supply chain is briefly outlined. Keywords: Air quality, Biomass, Climate change, Forest fires, Particulate matter, Wildfires

A series of analogues of Amb639752, a novel diacylglycerol kinase (DGK) inhibitor recently discovered by us via virtual screening, have been tested. The compounds were evaluated as DGK inhibitors on α, θ, and ζ isoforms, and as antagonists on serotonin receptors. From these assays emerged two novel compounds, namely 11 and 20, which with an IC50 respectively of 1.6 and 1.8 µM are the most potent inhibitors of DGKα discovered to date. Both compounds demonstrated the ability to restore apoptosis in a cellular model of X-linked lymphoproliferative disease as well as the capacity to reduce the migration of cancer cells, suggesting their potential utility in preventing metastasis. Finally, relying on experimental biological data, molecular modelling studies allow us to set a three-point pharmacophore model for DGK inhibitors.

This dialogue with Luca Mercalli, researcher and science communicator of environmental issues, focuses on the link between climate change and migration, with a particular reference to what is currently happening here and there in Italian mountains. It is a sort of ‘upwelling’ towards mountain areas whose protagonists (new mountaineers) try to fulfil not only an economic but also a life project. Mercalli explains the reasons of this movement towards the mountains which, in the next future, will become an increasingly central issue in territorial policies, telling his personal experience and choice to live in the upper Susa valley, in the borough of Vazon (Oulx). A complex challenge, this, between struggles and the great beauty expressed in that place. Attention and regard to the place accompany his project both in re-functionalizing and in building technique choices. A sort of ship’s log that helps reflect on the urgent programmes and policies for the re-activation of mountain territories.

Aim. The aim of the current study was to compare clinical characteristics, laboratory findings, and major outcomes of patients hospitalized for COVID-19 pneumonia with COVID-associated hyperglycaemia or pre-existing diabetes. Methods. A cohort of 176 adult patients with a diagnosis of pre-existing diabetes (n = 112) or COVID-associated hyperglycaemia (n = 55) was studied. Results. Patients with COVID-associated hyperglycaemia had lower BMI, significantly less comorbidities, and higher levels of inflammatory markers and indicators of multi-organ injury than those with pre-existing diabetes. No differences between pre-existing diabetes and COVID-associated hyperglycaemia were evident for symptoms at admission, the humoral response against SARS-CoV-2, or autoantibodies to glutamic acid decarboxylase or interferon alpha-4. COVID-associated hyperglycaemia was independently associated with the risk of adverse clinical outcome, which was defined as ICU admission or death (HR 2.11, 95% CI 1.34–3.31; p = 0.001), even after adjustment for age, sex, and other selected variables associated with COVID-19 severity. Furthermore, at the same time, we documented a negative association (HR 0.661, 95% CI 0.43–1.02; p = 0.063) between COVID-associated hyperglycaemia to swab negativization. Conclusions. Recognizing hyperglycaemia as a specific clinical entity associated with COVID-19 pneumonia is relevant for early and appropriate patient management and close monitoring for the progression of disease severity.

Telemedicine can provide benefits in patient affected by chronic diseases or elderly citizens as part of standard routine care supported by digital health. The GATEKEEPER (GK) Project was financed to create a vendor independent platform to be adopted in medical practice and to demonstrate its effect, benefit value, and scalability in 8 connected medical use cases with some independent pilots. This paper, after a description of the GK platform architecture, is focused on the creation of a FHIR (Fast Healthcare Interoperability Resource) IG (Implementation Guide) and its adoption in specific use cases. The final aim is to combine conventional data, collected in the hospital, with unconventional data, coming from wearable devices, to exploit artificial intelligence (AI) models designed to evaluate the effectiveness of a new parsimonious risk prediction model for Type 2 diabetes (T2D). [ABSTRACT FROM AUTHOR]