In Vitro Evaluation of Graft-versus-Graft Alloreactivity as a Tool to Identify the Predominant Cord Blood Unit before Double Cord Blood Transplantation

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Immunopathological signatures in multisystem inflammatory syndrome in children and pediatric COVID-19

: Pediatric Coronavirus Disease 2019 (pCOVID-19) is rarely severe; however, a minority of children infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) might develop multisystem inflammatory syndrome in children (MIS-C), with substantial morbidity. In this longitudinal multi-institutional study, we applied multi-omics (analysis of soluble biomarkers, proteomics, single-cell gene expression and immune repertoire analysis) to profile children with COVID-19 (n = 110) and MIS-C (n = 76), along with pediatric healthy controls (pHCs; n = 76). pCOVID-19 was characterized by robust type I interferon (IFN) responses, whereas prominent type II IFN-dependent and NF-κB-dependent signatures, matrisome activation and increased levels of circulating spike protein were detected in MIS-C, with no correlation with SARS-CoV-2 PCR status around the time of admission. Transient expansion of TRBV11-2 T cell clonotypes in MIS-C was associated with signatures of inflammation and T cell activation. The association of MIS-C with the combination of HLA A*02, B*35 and C*04 alleles suggests genetic susceptibility. MIS-C B cells showed higher mutation load than pCOVID-19 and pHC. These results identify distinct immunopathological signatures in pCOVID-19 and MIS-C that might help better define the pathophysiology of these disorders and guide therapy

Machine Learning in Hypertension Detection: A Study on World Hypertension Day Data

Many modifiable and non-modifiable risk factors have been associated with hypertension. However, current screening programs are still failing in identifying individuals at higher risk of hypertension. Given the major impact of high blood pressure on cardiovascular events and mortality, there is an urgent need to find new strategies to improve hypertension detection. We aimed to explore whether a machine learning (ML) algorithm can help identifying individuals predictors of hypertension. We analysed the data set generated by the questionnaires administered during the World Hypertension Day from 2015 to 2019. A total of 20206 individuals have been included for analysis. We tested five ML algorithms, exploiting different balancing techniques. Moreover, we computed the performance of the medical protocol currently adopted in the screening programs. Results show that a gain of sensitivity reflects in a loss of specificity, bringing to a scenario where there is not an algorithm and a configuration which properly outperforms against the others. However, Random Forest provides interesting performances (0.818 sensitivity – 0.629 specificity) compared with medical protocols (0.906 sensitivity – 0.230 specificity). Detection of hypertension at a population level still remains challenging and a machine learning approach could help in making screening programs more precise and cost effective, when based on accurate data collection. More studies are needed to identify new features to be acquired and to further improve the performances of ML models

Amblyomma parvum Aragão, 1908 (Acari: Ixodidae): Phylogeography and systematic considerations

The geographical distribution of Amblyomma parvum Aragão 1908 in the New World is disjunct, with two main clusters separated from each other by the Amazon basin. The main objectives of this study were to further investigate the systematic relationships within A. parvum, to determine whether or not populations from different geographical areas might represent cryptic species, and to reconstruct the phylogeographical evolutionary history of the species. The genetic diversity of A. parvum collected throughout its distributional range was analyzed by using 6 molecular markers: 5 mitochondrial [the small and the large ribosomal subunits 12rDNA and 16SrDNA, the cytochrome oxidase I (COI) and II (COII) and the control region or d-loop (DL)], and one nuclear (ITS2, Inter transcribed spacer 2). Phylogenetic trees were inferred by using maximum parsimony and Bayesian analyses. In addition, node dating was attempted for the main lineages identified phylogenetically. Although mitochondrial and nuclear topologies were not totally congruent, they all identified at least two main supported clusters, a Central American lineage, and a Brazilian-Argentinian lineage. Clade support and divergence values strongly suggest that the two lineages correspond to different taxonomic entities. Node dating placed the split between the Central American and the Brazilian-Argentinian lineages at approximately 5.8–4.9 Mya, just after the progressive replacement of the dry areas that occupied the northern part of South America by the Amazon Basin in the early-mid Miocene. This event might be the cause of fragmentation and putative speciation within the ancestral relatively xerophilic A. parvum population.EEA RafaelaFil: Lado, Paula. Georgia Southern University. Institute for Coastal Plain Science. United States National Tick Collection; Estados UnidosFil: Nava, Santiago. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Rafaela; ArgentinaFil: Labruna, Marcelo B. Universidade de São Paulo. Faculdade de Medicina Veterinária e Zootecnia. Departamento de Medicina Veterinária Preventiva e Saúde Animal; BrasilFil: Szabó, Matías P.J. Universidade Federal de Uberlandia. Faculdade de Medicina Veterinaria e Zootecnia; BrasilFil: Durden, Lance A. Georgia Southern University. Biology Department; Estados UnidosFil: Bermudez, Sergio. Instituto Conmemorativo Gorgas de Estudios de la Salud. Departamento de Investigación en Entomología Médica; PanamáFil: Montagna, Matteo. Università degli Studi di Milano. Dipartamento di Scienze Agrarie e Ambientali; ItaliaFil: Sánchez Quirós, Ana C. Universidad de Costa Rica. Escuela de Biología; Costa RicaFil: Beati, Lorenza. Georgia Southern University. Institute for Coastal Plain Science. United States National Tick Collection; Estados Unido

Impact of passive smoke and/or atopy on adenoid immunoglobulin production in children

The adenoids are exposed to a wide number and variety of microbes, environmental pollutants, and food antigens. Atopy and passive smoke may significantly affect immune responses, mainly in children. The aim of the present study was to investigate whether passive exposure to tobacco smoke and/or atopy could affect immunoglobulin production by adenoidal lymphocytes in a cohort of children presenting with adenoid hypertrophy. A total of 277 children (151 males and 126 females; median age 5.5 years), with adenoidal hypertrophy requiring adenoidectomy and or adeno-tonsillectomy, were consecutively enrolled in the study. Adenoid mononuclear cells were in vitro stimulated with LPS or CpG. When considering both the presence of smoke exposure and atopy, we observed that the CpG-induced decrease in IgA and IgM production was significantly associated with this combination of risk factors. In the T-independent immunoglobulin production assay we found a positive association between the two risk factors and IgA and IgM production. In particular, the presence of both risk factors, showed a significant increase in IgA and IgM production after stimulation. In conclusion, this is the first study that investigated the in vitro adenoidal B cell response after different stimuli in children, also evaluating possible exposure to passive smoke and/or an atopic condition