Background The pathogenesis of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection remains unclear. We report the detection of viral RNA from different anatomical districts and the antibody profile in the first two COVID-19 cases diagnosed in Italy Methods We tested for SARS-CoV-2 RNA clinical samples, either respiratory and non-respiratory (i.e. saliva, serum, urine, vomit, rectal, ocular, cutaneous, and cervico-vaginal swabs), longitudinally collected from both patients throughout the hospitalization. Serological analysis was carried out on serial serum samples to evaluate IgM, IgA, IgG and neutralizing antibodies levels Results SARS-CoV-2 RNA was detected since the early phase of illness lasting over two weeks in both upper and lower respiratory tract samples. Virus isolate was obtained from acute respiratory sample, while no infectious virus was rescued from late respiratory samples with low viral RNA load, collected when serum antibodies had been developed. Several other specimens resulted positive including saliva, vomit, rectal, cutaneous, cervico-vaginal, and ocular swabs. Specific IgM, IgA and IgG were detected within the first week since diagnosis, with IgG appearing earlier and at higher titres. Neutralizing antibodies developed during the second week, reaching high titres 32 days since diagnosis Conclusions Our longitudinally analysis showed that SARS-CoV-2 RNA can be detected in different body samples which may be associated with broad tropism and different spectra of clinical manifestations and modes of transmission. Profiling antibody response and neutralizing activity can assist laboratory diagnosis and surveillance actions
A graph G is a multi-interval PCG if there exist an edge weighted tree T with non-negative real values and disjoint intervals of the non-negative real half-line such that each node of G is uniquely associated to a leaf of T and there is an edge between two nodes in G if and only if the weighted distance between their corresponding leaves in T lies within any such intervals. If the number of intervals is k, then we call the graph a k-interval-PCG; in symbols, G = k-interval-PCG (T, I 1 , . . . , I k ).It is known that 2-interval-PCGs do not contain all graphs and the smallest known graph outside this class has 135 nodes. Here we prove that all graphs with at most 8 nodes are 2-interval-PCGs, so doing one step towards the determination of the smallest value of n such that there exists an n node graph that is not a 2-interval-PCG.
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