Radiation risks knowledge in resident and fellow in paediatrics: A questionnaire survey

Background: Analyse through a multi-choice anonymous questionnaire the knowledge's level in paediatric residents and fellows in two different main Italian hospital, looking mainly to the information to patients and relatives related to risks of ionizing radiation used in common radiological investigations in children. Methods: 65 multi choice questionnaires were distributed to paediatric residents and fellows of two different hospitals, an University Hospital (A.O.U.P. "P. Giaccone"- University of Palermo) and a national reference centre for paediatrics (Ospedale Pediatrico Bambino Gesù - Rome). The questionnaire included twelve multiple-choice questions with the aim of analyzing the knowledge about ionizing radiation related risks in infants and children who undergo common diagnostic radiology investigations. The data obtained were processed using software Stata/MP version 11.2. In order to measure the level of expertise of each interviewee a binary indicator was built. The value 1 was assigned if the percentage of correct answers exceeds the median of the distribution and 0 for values not exceeding the median. The association between the level of competence and demographic characteristics (gender, age) and training experience was measured by means of α2 test. Results: 51/65 questionnaires were completed, returned and analysed (87.7%). Only 18 surveyed (35%), (95% IC=[22%-48%]) can be defined as competent in radiation risk knowledge for common radiological investigations, considering the percentage of correct answers at least of 50% (sufficient knowledge was given with a minimum score of 8 correct answers out of 12). Conclusions: The study demonstrates an urgent need to implement the radiation protection knowledge in the training programme of paediatricians, that improve if just a short targeted training is performed

Immune cell profiling of the cerebrospinal fluid enables the characterization of the brain metastasis microenvironment

Brain metastases are the most common tumor of the brain with a dismal prognosis. A fraction of patients with brain metastasis benefit from treatment with immune checkpoint inhibitors (ICI) and the degree and phenotype of the immune cell infiltration has been used to predict response to ICI. However, the anatomical location of brain lesions limits access to tumor material to characterize the immune phenotype. Here, we characterize immune cells present in brain lesions and matched cerebrospinal fluid (CSF) using single-cell RNA sequencing combined with T cell receptor genotyping. Tumor immune infiltration and specifically CD8 + T cell infiltration can be discerned through the analysis of the CSF. Consistently, identical T cell receptor clonotypes are detected in brain lesions and CSF, confirming cell exchange between these compartments. The analysis of immune cells of the CSF can provide a non-invasive alternative to predict the response to ICI, as well as identify the T cell receptor clonotypes present in brain metastasis. The use of CSF for diagnosis of metastatic brain tumors could be of clinical and patient benefit. Here the authors undertake a single-cell RNA analysis of CSF and brain to determine whether the phenotype in the CSF is reflective of the phenotype in the tumo

Serum Albumin Is Inversely Associated With Portal Vein Thrombosis in Cirrhosis

We analyzed whether serum albumin is independently associated with portal vein thrombosis (PVT) in liver cirrhosis (LC) and if a biologic plausibility exists. This study was divided into three parts. In part 1 (retrospective analysis), 753 consecutive patients with LC with ultrasound-detected PVT were retrospectively analyzed. In part 2, 112 patients with LC and 56 matched controls were entered in the cross-sectional study. In part 3, 5 patients with cirrhosis were entered in the in vivo study and 4 healthy subjects (HSs) were entered in the in vitro study to explore if albumin may affect platelet activation by modulating oxidative stress. In the 753 patients with LC, the prevalence of PVT was 16.7%; logistic analysis showed that only age (odds ratio [OR], 1.024; P = 0.012) and serum albumin (OR, -0.422; P = 0.0001) significantly predicted patients with PVT. Analyzing the 112 patients with LC and controls, soluble clusters of differentiation (CD)40-ligand (P = 0.0238), soluble Nox2-derived peptide (sNox2-dp; P < 0.0001), and urinary excretion of isoprostanes (P = 0.0078) were higher in patients with LC. In LC, albumin was correlated with sCD4OL (Spearman's rank correlation coefficient [r(s)], -0.33; P < 0.001), sNox2-dp (r(s), -0.57; P < 0.0001), and urinary excretion of isoprostanes (r(s), -0.48; P < 0.0001) levels. The in vivo study showed a progressive decrease in platelet aggregation, sNox2-dp, and urinary 8-iso prostaglandin F2 alpha-III formation 2 hours and 3 days after albumin infusion. Finally, platelet aggregation, sNox2-dp, and isoprostane formation significantly decreased in platelets from HSs incubated with scalar concentrations of albumin. Conclusion: Low serum albumin in LC is associated with PVT, suggesting that albumin could be a modulator of the hemostatic system through interference with mechanisms regulating platelet activation

Post-transcriptional regulation of Alpha-synuclein and link to Parkinson's disease

The role of RNA processing in the pathogenesis of neurodegenerative diseases is still poorly understood. α-synuclein (SNCA) is a presynaptic neuronal protein known as the major component of Lewy bodies, the pathological hallmark of Parkinson’s disease (PD). Recent evidence suggests a link between the pathogenesis of PD and the expression of SNCA mRNA isoforms with 3’ untranslated region (3’UTR) of different lengths. The purpose of my doctoral studies was the discovery of RNA-binding proteins (RBPs) regulating SNCA at the post-transcriptional level. Using computational and experimental approaches, I identified a number of trans-acting elements that physically interact with SNCA and potentially control its metabolism. I especially focused on the characterization of two RBPs, ELAVL1 and TIAR, and showed their implication in SNCA mRNA stability and translation efficiency. These two factors might play important roles in the maintenance of α-synuclein level and functionality in physiological and pathological conditions.Se sap ben poc sobre el paper del processament del RNA en la patogènesi de les malalties neurodegeneratives. L’α-sinucleïna (SNCA) és una proteïna neuronal presinàptica i el principal component dels cossos de Lewy, que al seu torn són la troballa patològica característica en la malaltia de Parkinson (MP). Recentment s’ha suggerit un lligam entre la patogènesi de la MP i l’expressió d’isoformes del mRNA de SNCA amb diferents longituds de les regions de 3’ no traduïdes (en anglès conegudes com a untranslated regions UTRs). El propòsit dels meus estudis de doctorat és descobrir les proteïnes que uneixen el RNA de SNCA i el regulen a nivell posttranscripcional. Gràcies a una combinació d’estratègies computacionals i experimentals he identificat elements que interaccionen físicament amb SNCA i potencialment en regulen el metabolisme actuant en trans. M’he centrat en la caracterització de dues proteïnes que uneixen RNA, ELAVL1 i TIAR, i mostro la seva implicació en la regulació de l’estabilitat del mRNA i l’eficiència en la seva traducció. Aquestes dues proteïnes podrien tenir un paper clau en el manteniment dels nivells de α-sinucleïna i la seva funció en condicions fisiològiques i patològiques

Post-transcriptional regulation of Alpha-synuclein and link to Parkinson's disease

The role of RNA processing in the pathogenesis of neurodegenerative diseases is still poorly understood. α-synuclein (SNCA) is a presynaptic neuronal protein known as the major component of Lewy bodies, the pathological hallmark of Parkinson’s disease (PD). Recent evidence suggests a link between the pathogenesis of PD and the expression of SNCA mRNA isoforms with 3’ untranslated region (3’UTR) of different lengths. The purpose of my doctoral studies was the discovery of RNA-binding proteins (RBPs) regulating SNCA at the post-transcriptional level. Using computational and experimental approaches, I identified a number of trans-acting elements that physically interact with SNCA and potentially control its metabolism. I especially focused on the characterization of two RBPs, ELAVL1 and TIAR, and showed their implication in SNCA mRNA stability and translation efficiency. These two factors might play important roles in the maintenance of α-synuclein level and functionality in physiological and pathological conditions.Se sap ben poc sobre el paper del processament del RNA en la patogènesi de les malalties neurodegeneratives. L’α-sinucleïna (SNCA) és una proteïna neuronal presinàptica i el principal component dels cossos de Lewy, que al seu torn són la troballa patològica característica en la malaltia de Parkinson (MP). Recentment s’ha suggerit un lligam entre la patogènesi de la MP i l’expressió d’isoformes del mRNA de SNCA amb diferents longituds de les regions de 3’ no traduïdes (en anglès conegudes com a untranslated regions UTRs). El propòsit dels meus estudis de doctorat és descobrir les proteïnes que uneixen el RNA de SNCA i el regulen a nivell posttranscripcional. Gràcies a una combinació d’estratègies computacionals i experimentals he identificat elements que interaccionen físicament amb SNCA i potencialment en regulen el metabolisme actuant en trans. M’he centrat en la caracterització de dues proteïnes que uneixen RNA, ELAVL1 i TIAR, i mostro la seva implicació en la regulació de l’estabilitat del mRNA i l’eficiència en la seva traducció. Aquestes dues proteïnes podrien tenir un paper clau en el manteniment dels nivells de α-sinucleïna i la seva funció en condicions fisiològiques i patològiques

A computational approach for the discovery of protein-RNA networks

Protein–RNA interactions play important roles in a wide variety of cellular processes, ranging from transcriptional and posttranscriptional regulation of genes to host defense against pathogens. In this chapter we present the computational approach catRAPID to predict protein–RNA interactions and discuss how it could be used to find trends in ribonucleoprotein networks. We envisage that the combination of computational and experimental approaches will be crucial to unravel the role of coding and noncoding RNAs in protein networks

Single-cell multi-omics analysis of COVID-19 patients with pre-existing autoimmune diseases shows aberrant immune responses to infection

In COVID-19, hyperinflammatory and dysregulated immune responses contribute to severity. Patients with pre-existing autoimmune conditions can therefore be at increased risk of severe COVID-19 and/or associated sequelae, yet SARS-CoV-2 infection in this group has been little studied. Here, we performed single-cell analysis of peripheral blood mononuclear cells from patients with three major autoimmune diseases (rheumatoid arthritis, psoriasis, or multiple sclerosis) during SARS-CoV-2 infection. We observed compositional differences between the autoimmune disease groups coupled with altered patterns of gene expression, transcription factor activity, and cell-cell communication that substantially shape the immune response under SARS-CoV-2 infection. While enrichment of HLA-DRlow CD14+ monocytes was observed in all three autoimmune disease groups, type-I interferon signaling as well as inflammatory T cell and monocyte responses varied widely between the three groups of patients. Our results reveal disturbed immune responses to SARS-CoV-2 in patients with pre-existing autoimmunity, highlighting important considerations for disease treatment and follow-up.This research was funded/supported by the R+D+i project of the Spanish Ministry of Science and Innovation (grant number PID2020-117212RB-I00/ MICIN/AEI/10.13039/501100011033), the Chan Zuckerberg Initiative (grant 2020–216799) and Wellcome Sanger core funding (WT206194). This publication has been supported by the Unstoppable campaign of the Josep Carreras Leukaemia Foundation. B.G., F.J.C.-N., and N.K.W. were funded by Wellcome (206328/Z/17/Z), the MRC (MR/S036113/1), and the Aging Biology Foundation

A computational approach for the discovery of protein-RNA networks

Protein–RNA interactions play important roles in a wide variety of cellular processes, ranging from transcriptional and posttranscriptional regulation of genes to host defense against pathogens. In this chapter we present the computational approach catRAPID to predict protein–RNA interactions and discuss how it could be used to find trends in ribonucleoprotein networks. We envisage that the combination of computational and experimental approaches will be crucial to unravel the role of coding and noncoding RNAs in protein networks

Macrophage and neutrophil heterogeneity at single-cell spatial resolution in human inflammatory bowel disease

Ulcerative colitis and Crohn's disease are chronic inflammatory intestinal diseases with perplexing heterogeneity in disease manifestation and response to treatment. While the molecular basis for this heterogeneity remains uncharacterized, single-cell technologies allow us to explore the transcriptional states within tissues at an unprecedented resolution which could further understanding of these complex diseases. Here, we apply single-cell RNA-sequencing to human inflamed intestine and show that the largest differences among patients are present within the myeloid compartment including macrophages and neutrophils. Using spatial transcriptomics in human tissue at single-cell resolution (CosMx Spatial Molecular Imaging) we spatially localize each of the macrophage and neutrophil subsets identified by single-cell RNA-sequencing and unravel further macrophage diversity based on their tissue localization. Finally, single-cell RNA-sequencing combined with single-cell spatial analysis reveals a strong communication network involving macrophages and inflammatory fibroblasts. Our data sheds light on the cellular complexity of these diseases and points towards the myeloid and stromal compartments as important cellular subsets for understanding patient-to-patient heterogeneity.This work was funded by grant PID2021-123918OB-I00 from MCIN/AEI/ 10.13039/501100011033 and co-funded by “FEDER A way to make Europe”. AM-C, VG and ID were funded by grant Grant #2008-04050 from The Leona and Harry B. Helmsley Charitable Trust. EM-A is funded by grant RH042155 (RTI2018-096946-B-I00) from Ministerio de Ciencia e Innovacion. IA-T is funded by grant 831434-2 (CE_IMI2-2018-14 call). HH received support for the project PID2020-115439GB-I00- funded by MCIN/AEI/10.13039/501100011033. This publication is part of a project that has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 831434. This project also has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 848028