When the Fourth Estate Becomes a Fifth Column: The Effect of Media Freedom and Social Intolerance on Civil Conflict

Media freedom is typically viewed as crucial to democracy and development. The idea is that independent news media will facilitate free and fair elections and shine a spotlight on corruption—thereby serving as a fourth estate. Yet political leaders often justify restricting media freedom on the grounds that irresponsible news coverage will incite political violence—potentially undermining government and in effect acting as a fifth column. So is media freedom a force for democracy or a source of civil conflict? We hypothesize that the effect of media freedom on civil conflict is conditioned by a country’s level of intolerance. Specifically, we predict when social intolerance is low, media freedom will discourage domestic conflict because the tone of the news coverage will reflect the level of tolerance and ameliorate any inflammatory coverage. In contrast, we predict that high levels of social intolerance will fuel and be fueled by inflammatory news coverage if the media are free, thereby promoting civil conflict. We test our hypotheses across countries and over time drawing from World Values and European Values Surveys and the Global Media Freedom Dataset and find that the combination of media freedom and high social intolerance is associated with increased civil conflict

Photophobia and migraine outcome during treatment with galcanezumab

BackgroundCalcitonin gene-related peptide (CGRP) plays a pivotal role in migraine physiology, not only regarding migraine pain but also associated symptoms such as photophobia. The aim of the present study was to assess monoclonal antibodies targeting CGRP efficacy not only in terms of headache and migraine frequency and disability but also in reducing ictal photophobia.Material and methodsThis is a retrospective observational study, conducted at the Headache Center–ASST Spedali Civili Brescia. All patients in monthly treatment with galcanezumab with at least a 6-month follow-up in September 2022 with reported severe photophobia during migraine attacks were included. Data regarding headache frequency, analgesics consumption, and migraine disability were collected quarterly. Moreover, patients were asked the following information regarding photophobia: (1) whether they noticed an improvement in photophobia during migraine attacks since galcanezumab introduction; (2) the degree of photophobia improvement (low, moderate, and high); and (3) timing photophobia improvement.ResultsForty-seven patients were enrolled in the present study as they met the inclusion criteria. Seventeen patients had a diagnosis of high-frequency episodic migraine and 30 of chronic migraine. From baseline to T3 and T6, a significant improvement in terms of headache days (19.2 ± 7.6 vs. 8.6 ± 6.8 vs. 7.7 ± 5.7; p < 0.0001), migraine days (10.4 ± 6.7 vs. 2.9 ± 4.3 vs. 3.6 ± 2.8; p < 0.0001), analgesics consumption (25.1 ± 28.2 vs. 7.6 ± 7.5 vs. 7.6 ± 8.1; p < 0.0001), MIDAS score (82.1 ± 48.4 vs. 21.6 ± 17.6 vs. 18.1 ± 20.5; p < 0.0001), and HIT-6 score (66.2 ± 6.2 vs. 57.2 ± 8.6 vs. 56.6 ± 7.6; p < 0.0001) was found. Thirty-two patients (68.1%) reported a significant improvement in ictal photophobia, with over half of the patients reporting it within the first month of treatment. Photophobia improvement was more frequent in patients with episodic migraine (p = 0.02) and triptans responders (p = 0.03).ConclusionsThe present study confirms previous reports regarding galcanezumab efficacy beyond migraine frequency. In particular, over 60% of patients, in our cohort, documented a significant improvement also in reducing ictal photophobia. This improvement was, in most patients, moderate to high, and within the first 6 months of treatment, regardless of the clinical response on migraine frequency

Seroprevalence of Bartonella henselae in patients awaiting heart transplant in Southern Italy

Background Bartonella henselae is the etiologic agent of cat-scratch disease. B. henselae infections are responsible for a widening spectrum of human diseases, although often symptomless, ranging from self-limited to life-threatening and show different courses and organ involvement due to the balance between host and pathogen. The role of the host immune response to B. henselae is critical in preventing progression to systemic disease. Indeed in immunocompromised patients, such as solid organ transplant patients, B. henselae results in severe disseminated disease and pathologic vasoproliferation. The purpose of this study was to determine the seroprevalence of B. henselae in patients awaiting heart transplant compared to healthy individuals enrolled in the Regional Reference Laboratory of Transplant Immunology of Second University of Naples. Methods Serum samples of 38 patients awaiting heart transplant in comparison to 50 healthy donors were examined using immunfluorescence assay. Results We found a B. henselae significant antibody positivity rate of 21% in patients awaiting heart transplant ( p = 0.002). There was a positive rate of 8% ( p > 0.05) for immunoglobulin (Ig)M and a significant value of 13% ( p = 0.02) for IgG, whereas controls were negative both for IgM and IgG antibodies against B. henselae . The differences in comorbidity between cases and controls were statistically different (1.41 ± 0.96 vs 0.42 ± 0.32; p = 0.001). Conclusions Although this study was conducted in a small number of patients, we suggest that the identification of these bacteria should be included as a routine screening analysis in pretransplant patients

Does compulsory vaccination limit personal freedom? Ethical issues

BackgroundDespite vaccinations are scientifically proven to be safe and effective public controversies limit their application in many countries.AimsAim of this review is to provide an overview of biological effects of vaccination and a picture of the ethical dilemmas about compulsory vaccination.Methods We conducted a review on the literature about the subject. Recent news were also included.Results Vaccines are the best weapon against many infectious diseases. The spread of false beliefs among people have led the government authorities to increase compulsory vaccination in order to embank new outbreaks of preventable infectious diseases.ConclusionEven if compulsory is quite drastic approach it could be the on only way to reach an adequate coverage and protect immunoexpressed subjects

Differential epigenetic factors in the prediction of cardiovascular risk in diabetic patients

Hyperglycaemia can strongly alter the epigenetic signatures in many types of human vascular cells providing persistent perturbations of protein-protein interactions both in micro- and macro-domains. The establishment of these epigenetic changes may precede cardiovascular (CV) complications and help us to predict vascular lesions in diabetic patients. Importantly, these epigenetic marks may be transmitted across several generations (transgenerational effect) and increase the individual risk of disease. Aberrant DNA methylation and imbalance of histone modifications, mainly acetylation and methylation of H3, represent key determinants of vascular lesions and, thus, putative useful biomarkers for prevention and diagnosis of CV risk in diabetics. Moreover, a differential expression of some micro-RNAs (miRNAs), mainly miR-126, may be a useful prognostic biomarker for atherosclerosis development in asymptomatic subjects. Recently, also environmental-induced chemical perturbations in mRNA (epitranscriptome), mainly the N6-methyladenosine, have been associated with obesity and diabetes. Importantly, reversal of epigenetic changes by modulation of lifestyle and use of metformin, statins, fenofibrate, and apabetalone may offer useful therapeutic options to prevent or delay CV events in diabetics increasing the opportunity for personalized therapy. Network medicine is a promising molecular-bioinformatic approach to identify the signalling pathways underlying the pathogenesis of CV lesions in diabetic patients. Moreover, machine learning tools combined with tomography are advancing the individualized assessment of CV risk in these patients. We remark the need for combining epigenetics and advanced bioinformatic platforms to improve the prediction of vascular lesions in diabetics increasing the opportunity for CV precision medicine

Exploring Unsupervised Learning Techniques for the Internet of Things

Nowadays, machine learning (ML) techniques can provide new perspectives to identify hidden patterns and classes inside data. Applying ML to the Internet of Things (IoT) and its produced data represents a great challenge in every application domain, since analyzing IoT data increasingly requires the use of advanced mathematical algorithms, novel computational techniques, and services. In this article, we present and discuss the application of unsupervised learning techniques on IoT data collected in a cultural heritage framework. Behavioral data have been gathered in a noninvasive way in order to achieve an ML classification that can be exploited by cultural stakeholders in terms of the medium-to long-term strategy and also in terms of strictly operational decisions. The application of ML and other learning techniques will acquire a key role to complement the more traditional services with new intelligent ones able to satisfy the needs of companies, stakeholders, and consumers

Path prediction in IoT systems through Markov Chain algorithm

In the Data Technology Era, inferring knowledge from data is an ubiquitous and pervasive research topic. Digital Ecosystems based on the Internet of Things (IoT) are generally designed for generating and collecting complex, real-time and (un)structured data. As one of the main component of the Smart City framework, the huge amount of IoT data has to be opportunely processed, also through Machine Learning algorithms in order to discover new knowledge and to improve the quality-of-life of the citizens. In our research work we propose some learning methodologies to analyse and forecast visitors’ paths within a cultural and complex space. Starting from data collected in a museum equipped with a non-invasive monitoring IoT system, we show how it is possible to discover and predict useful information on visitors’ movements and, finally, we present and discuss some useful insights on their behaviours within a real case-of-study

Hybrid 18F-FDG-PET/MRI Measurement of Standardized Uptake Value Coupled with Yin Yang 1 Signature in Metastatic Breast Cancer. A Preliminary Study

Detection of breast cancer (BC) metastasis at the early stage is important for the assessment of BC progression status. Image analysis represents a valuable tool for the management of oncological patients. Our preliminary study combined imaging parameters from hybrid 18F-FDG-PET/MRI and the expression level of the transcriptional factor Yin Yang 1 (YY1) for the detection of early metastases

Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next

Physics-Informed Neural Networks (PINN) are neural networks (NNs) that encode model equations, like Partial Differential Equations (PDE), as a component of the neural network itself. PINNs are nowadays used to solve PDEs, fractional equations, integral-differential equations, and stochastic PDEs. This novel methodology has arisen as a multi-task learning framework in which a NN must fit observed data while reducing a PDE residual. This article provides a comprehensive review of the literature on PINNs: while the primary goal of the study was to characterize these networks and their related advantages and disadvantages. The review also attempts to incorporate publications on a broader range of collocation-based physics informed neural networks, which stars form the vanilla PINN, as well as many other variants, such as physics-constrained neural networks (PCNN), variational hp-VPINN, and conservative PINN (CPINN). The study indicates that most research has focused on customizing the PINN through different activation functions, gradient optimization techniques, neural network structures, and loss function structures. Despite the wide range of applications for which PINNs have been used, by demonstrating their ability to be more feasible in some contexts than classical numerical techniques like Finite Element Method (FEM), advancements are still possible, most notably theoretical issues that remain unresolved