Machine Learning Approaches in Diagnosis, Prognosis and Treatment Selection of Cardiac Amyloidosis.

Cardiac amyloidosis is an uncommon restrictive cardiomyopathy featuring an unregulated amyloid protein deposition that impairs organic function. Early cardiac amyloidosis diagnosis is generally delayed by indistinguishable clinical findings of more frequent hypertrophic diseases. Furthermore, amyloidosis is divided into various groups, according to a generally accepted taxonomy, based on the proteins that make up the amyloid deposits; a careful differentiation between the various forms of amyloidosis is necessary to undertake an adequate therapeutic treatment. Thus, cardiac amyloidosis is thought to be underdiagnosed, which delays necessary therapeutic procedures, diminishing quality of life and impairing clinical prognosis. The diagnostic work-up for cardiac amyloidosis begins with the identification of clinical features, electrocardiographic and imaging findings suggestive or compatible with cardiac amyloidosis, and often requires the histological demonstration of amyloid deposition. One approach to overcome the difficulty of an early diagnosis is the use of automated diagnostic algorithms. Machine learning enables the automatic extraction of salient information from "raw data" without the need for pre-processing methods based on the a priori knowledge of the human operator. This review attempts to assess the various diagnostic approaches and artificial intelligence computational techniques in the detection of cardiac amyloidosis.

COVID-19 pandemic: different roles for scientific publications and funding face to epidemiological data-an European, country-based perspective.

COVID-19 has represented an unprecedented challenge to be faced also concerning the spread of information, with scientific literature being often the sole source of trustworthy knowledge for the global community. However, a massive waste in research was noticed during pandemic, preventing the scientists to produce totally novel and original results, and the citizenship to have the complete support they needed from science. The present work investigated the relationship between planned funding, research grants, scientific publications and epidemiology in the 27 EU countries, retrieving a significant correlation between scientific publications and COVID-19 cases and deaths, as well as with economic data. Interestingly, planned coronavirus-devoted funds were correlated with lower GDP per capita and higher mortality, leading to the hypothesis for a lack of translation into real funds allowed to the respective country, or for a significant research waste, not transformed into a tangible product or effect. Such results could suggest the need for a different approach in the future concerning the redistribution of research funds in case of COVID-19 relapse or future pandemic events.

MiR-21 upregulation increases IL-8 expression and tumorigenesis program in airway epithelial cells exposed to cigarette smoke.

BACKGROUND: Cigarette smoke exposure, increasing Toll-like receptor 4 (TLR4) and reactive oxygen species (ROS), promotes inflammatory responses in airway epithelial cells. Chronic inflammation, microRNA (miRNA), and oxidative stress are associated with cancer development. AIMS: The present study was aimed to explore whether cigarette smoke exposure, altering miR-21 expression, promoted inflammatory responses and tumorigenesis processes in airway epithelial cells. METHODS: Airway normal and cancer epithelial cells (16HBE and A549) were exposed to cigarette smoke extracts (CSE) or with/without agomiR-21, and then it was assessed: a) miR-21 expression; b) signal transducer and activator of transcription 3 (STAT3) nuclear protein expression and ERK1/2 activation; c) IL-8 gene expression and protein release. An antagonist of TLR4 (CLI-095) and the antioxidant flavonoid, apigenin, were also included to evaluate miR-21 expression in CSE exposed cells. RESULTS: It was demonstrated that: a) A549 cells constitutively expressed higher levels of miR-21 and IL-8; b) CSE increased STAT3 nuclear expression in 16HBE; c) in both cell lines, CSE and agomiR-21 increased: miR-21 expression; ERK1/2 activation and IL-8 gene expression and protein release; d) TLR4 inhibition counteracted the effects of CSE on miR-21 in A549; e) apigenin reduced miR-21 and IL-8 gene expression in both cell lines. CONCLUSIONS: Data herein provided identified for the first time new mechanisms supporting the crucial role of cigarette smoke-induced miR-21 expression in the amplification of inflammatory responses and in tumorigenesis processes within the airways.

Gender Differences in Oxidative Stress in Relation to Cancer Susceptibility and Survival.

Genetic, developmental, biochemical, and environmental variables interact intricately to produce sex differences. The significance of sex differences in cancer susceptibility is being clarified by numerous studies. Epidemiological research and cancer registries have revealed over the past few years that there are definite sex variations in cancer incidence, progression, and survival. However, oxidative stress and mitochondrial dysfunction also have a significant impact on the response to treatment of neoplastic diseases. Young women may be more protected from cancer than men because most of the proteins implicated in the regulation of redox state and mitochondrial function are under the control of sexual hormones. In this review, we describe how sexual hormones control the activity of antioxidant enzymes and mitochondria, as well as how they affect several neoplastic diseases. The molecular pathways that underlie the gender-related discrepancies in cancer that have been identified may be better understood, which may lead to more effective precision medicine and vital information on treatment options for both males and females with neoplastic illnesses.

"Mens Sana in Cute Sana"-A State of the Art of Mutual Etiopathogenetic Influence and Relevant Pathophysiological Pathways between Skin and Mental Disorders: An Integrated Approach to Contemporary Psychopathological Scenarios.

The negative socioeconomic impact of mental health disorders and skin diseases has increased in part due to the conflict between Russia and Ukraine, which has been a fertile ground for the emergence of psychopathologies. It is firmly established that there is a direct thread of etiopathogenetic communication between skin diseases and neuropsychiatric disorders, and the literature has tried to reveal the pathophysiological mechanisms governing such bidirectionality. This paper discusses this complex network of molecular pathways that are targeted by conventional and biological pharmacological agents that appear to impact two pathological spheres that previously seemed to have little connection. This molecular discussion is supplemented with a literature review, from a clinical viewpoint, regarding skin-brain etiopathogenetic bidirectionality. We focus on post-traumatic stress disorder (PTSD), which can be considered for all intents and purposes a systemic inflammatory disease that also affects the skin. A brief overview is also provided on the diagnostic-therapeutic and follow-up potential of oxidative and inflammatory markers potentially involved in the pathophysiological mechanisms treated. The aim is to clarify how these mechanisms may be useful in defining different stress-coping strategies and thus individual phenotypes of stress sensitivity/resistance in order to promote personalized medicine in the field of psychodermatology.

Upsides and downsides of a telecounselling model of integrated asthma management between general practitioners and specialists.

BACKGROUND: Asthma control, one of the most important goals in the management of asthmatic patients, requires good adherence to guidelines and support at a territorial level, in particular on the part of general practitioners (GPs). A territorial hospital alliance can become a strength in asthma management, where control by GPs can also be carried out through a spirometric examination. METHODS: The realisation of a telecounselling model management of asthma between GPs and specialists was the aim of this study, to understand how to obtain good asthma control. A specific digital platform, the PneumoApp platform, was used for the insertion of clinical data and flow volume (F-V) curves, performed in asthmatic patients by GPs, and for the subsequent evaluation of these data by specialists. RESULTS: GPs have shown to be able to perform a check-up of respiratory function well using a portable spirometer, but the analysis of the collected data showed that GP assessment of the severity level of asthma is incorrect in patients with moderate-severe asthma. CONCLUSIONS: The effectiveness of a telecounselling collaboration between hospital and territory in the management of asthma patients can be improved by greater diffusion of the use of Global Initiative for Asthma (GINA) guidelines at a local level.

Machine Learning and Deep Learning Applications in Multiple Myeloma Diagnosis, Prognosis, and Treatment Selection.

Artificial intelligence has recently modified the panorama of oncology investigation thanks to the use of machine learning algorithms and deep learning strategies. Machine learning is a branch of artificial intelligence that involves algorithms that analyse information, learn from that information, and then employ their discoveries to make abreast choice, while deep learning is a field of machine learning basically represented by algorithms inspired by the organization and function of the brain, named artificial neural networks. In this review, we examine the possibility of the artificial intelligence applications in multiple myeloma evaluation, and we report the most significant experimentations with respect to the machine and deep learning procedures in the relevant field. Multiple myeloma is one of the most common haematological malignancies in the world, and among them, it is one of the most difficult ones to cure due to the high occurrence of relapse and chemoresistance. Machine learning- and deep learning-based studies are expected to be among the future strategies to challenge this negative-prognosis tumour via the detection of new markers for their prompt discovery and therapy selection and by a better evaluation of its relapse and survival.

Psychological Interventions for Children with Autism during the COVID-19 Pandemic through a Remote Behavioral Skills Training Program.

COVID-19 has impacted negatively on the mental health of children with autism spectrum disorder (ASD), as well as on their parents. Remote health services are a sustainable approach to behavior management interventions and to giving caregivers emotional support in several clinical domains. During the COVID-19 pandemic, we investigated the feasibility of a web-based behavioral skills training (BST) program for 16 parents and their children with ASD at home. The BST parent training package was tailored to each different specific behavioral disorder that characterizes children with ASD. After training, we found a significant reduction in the frequency of all the targeted behavioral disorders, as well as an improvement in psychological distress and the perception of the severity of ASD-related symptoms in parents. Our data confirm the efficacy of remote health care systems in the management of behavioral disorders of children with ASD, as well as of their parents during the COVID-19 pandemic.

Mindfulness-Based Interventions for Physical and Psychological Wellbeing in Cardiovascular Diseases: A Systematic Review and Meta-Analysis.

BACKGROUND: Recently, there has been an increased interest in the efficacy of mindfulness-based interventions (MBI) for people with cardiovascular diseases (CVD), although the exact beneficial effects remain unclear. METHODS: This review aims to establish the role of MBI in the management of wellbeing for patients with CVD. Seventeen articles have been included in this systematic synthesis of the literature and eleven in the meta-analysis. RESULTS: Considering physical (i.e., heart rate, blood pressure) and psychological outcomes (i.e., depression, anxiety, stress, styles of coping), the vast majority of studies confirmed that MBI has a positive influence on coping with psychological risk factors, also improving physiological fitness. Random-effects meta-analysis models suggested a moderate-to-large effect size in reducing anxiety, depression, stress, and systolic blood pressure. CONCLUSIONS: Although a high heterogeneity was observed in the methodological approaches, scientific literature confirmed that MBI can now be translated into a first-line intervention tool for improving physical and psychological wellbeing in CVD patients.

Coopted temporal patterning governs cellular hierarchy, heterogeneity and metabolism in Drosophila neuroblast tumors.

It is still unclear what drives progression of childhood tumors. During Drosophila larval development, asymmetrically-dividing neural stem cells, called neuroblasts, progress through an intrinsic temporal patterning program that ensures cessation of divisions before adulthood. We previously showed that temporal patterning also delineates an early developmental window during which neuroblasts are susceptible to tumor initiation (Narbonne-Reveau et al., 2016). Using single-cell transcriptomics, clonal analysis and numerical modeling, we now identify a network of twenty larval temporal patterning genes that are redeployed within neuroblast tumors to trigger a robust hierarchical division scheme that perpetuates growth while inducing predictable cell heterogeneity. Along the hierarchy, temporal patterning genes define a differentiation trajectory that regulates glucose metabolism genes to determine the proliferative properties of tumor cells. Thus, partial redeployment of the temporal patterning program encoded in the cell of origin may govern the hierarchy, heterogeneity and growth properties of neural tumors with a developmental origin.