Vaccination against COVID-19 is the most effective tool to protect both the individual and the community from this potentially life-threatening infectious disease. Data from phase-3 trials showed that two doses of the BNT162b2 vaccine were safe, immunogenic, and effective against COVID-19 in children aged 5–11 years. However, no surveys in real-life settings have been carried out in this age range. Here, we conducted a cross-sectional study to evaluate the short-term adverse reactions (ARs) and the rate of protection against infection of the BNT162b2 vaccine in children aged 5–11 years by the compilation of two surveillance questionnaires conceived using Google Forms. Five-hundred and ninety one children were included in the analysis. ARs were reported by 68.9% of the children, being mainly local. The incidence of systemic ARs, especially fever, was higher after the second dose. The incidence of infection after completing the immunization accounted for 13.6% of the children. COVID-19 symptoms reported were mild, with the exception of one case of pneumonia. Only 40% of infected participants needed to take medication to relieve symptoms, mostly paracetamol and NSAIDs, and none reported persistent symptoms. The Pfizer–BioNTech vaccine in children aged 5–11 years is safe and well tolerated. The mild clinical course of COVID-19 in immunized children confirmed the favorable risk–benefit ratio, encouraging parents to immunize their children.

SARS-CoV-2 mRNA vaccines prevent severe COVID-19 by generating immune memory, comprising specific antibodies and memory B and T cells. Although children are at low risk of severe COVID-19, the spreading of highly transmissible variants has led to increasing in COVID-19 cases and hospitalizations also in the youngest, but vaccine coverage remains low. Immunogenicity to mRNA vaccines has not been extensively studied in children 5 to 11 years old. In particular, cellular immunity to the wild-type strain (Wuhan) and the cross-reactive response to the Omicron variant of concern has not been investigated. We assessed the humoral and cellular immune response to the SARS-CoV-2 BNT162b2 vaccine in 27 healthy children. We demonstrated that vaccination induced a potent humoral and cellular immune response in all vaccinees. By using spike-specific memory B cells as a measurable imprint of a previous infection, we found that 50% of the children had signs of a past, undiagnosed infection before vaccination. Children with pre-existent immune memory generated significantly increased levels of specific antibodies, and memory T and B cells, directed against not only the wild type virus but also the omicron variant.

Regional gravity field modelling by means of remove-compute-restore procedure is nowadays widely applied in different contexts: it is the most used technique for regional gravimetric geoid determination, and it is also used in exploration geophysics to predict grids of gravity anomalies (Bouguer, free-air, isostatic, etc.), which are useful to understand and map geological structures in a specific region. Considering this last application, due to the required accuracy and resolution, airborne gravity observations are usually adopted. However, due to the relatively high acquisition velocity, presence of atmospheric turbulence, aircraft vibration, instrumental drift, etc., airborne data are usually contaminated by a very high observation error. For this reason, a proper procedure to filter the raw observations in both the low and high frequencies should be applied to recover valuable information. In this work, a software to filter and grid raw airborne observations is presented: the proposed solution consists in a combination of an along-track Wiener filter and a classical Least Squares Collocation technique. Basically, the proposed procedure is an adaptation to airborne gravimetry of the Space-Wise approach, developed by Politecnico di Milano to process data coming from the ESA satellite mission GOCE. Among the main differences with respect to the satellite application of this approach, there is the fact that, while in processing GOCE data the stochastic characteristics of the observation error can be considered a-priori well known, in airborne gravimetry, due to the complex environment in which the observations are acquired, these characteristics are unknown and should be retrieved from the dataset itself. The presented solution is suited for airborne data analysis in order to be able to quickly filter and grid gravity observations in an easy way. Some innovative theoretical aspects focusing in particular on the theoretical covariance modelling are presented too. In the end, the goodness of the procedure is evaluated by means of a test on real data retrieving the gravitational signal with a predicted accuracy of about 0.4 mGal

Selective IgA deficiency (SIgAD) is the most common human primary immune deficiency (PID). It is classified as a humoral PID characterized by isolated deficiency of IgA (less than 7 mg/dL but normal serum IgG and IgM) in subjects greater than 4 years of age. Intrinsic defects in the maturation of B cells and a perturbation of Th cells and/or cytokine signals have been hypothesized to contribute to SIgAD pathogenesis. The genetic basis of IgA deficiency remains to be clarified. Patients with SIgAD can be either asymptomatic or symptomatic with clinical manifestations including allergy, autoimmunity and recurrent infections mainly of the respiratory and gastrointestinal tract. Studies analyzing allergy on SIgAD patients showed prevalence up to 84%, supporting in most cases the relationship between sIgAD and allergic disease. However, the prevalence of allergic disorders may be influenced by various factors. Thus, the question of whether allergy is more common in SIgAD patients compared to healthy subjects remains to be defined. Different hypotheses support an increased susceptibility to allergy in subjects with SIgAD. Recurrent infections due to loss of secretory IgA might have a role in the pathogenesis of allergy, and vice versa. Perturbation of microbiota also plays a role. The aim of this review is to examine the association between SIgAD and atopic disease and to update readers on advances over time at this important interface between allergy and SIgAD.

The computation of the vertical attraction due to the topographic masses, the so-called Terrain Correction, is a fundamental step in geodetic and geophysical applications: it is required in high-precision geoid estimation by means of the remove–restore technique and it is used to isolate the gravitational effect of anomalous masses in geophysical exploration. The increasing resolution of recently developed digital terrain models, the increasing number of observation points due to extensive use of airborne gravimetry in geophysical exploration and the increasing accuracy of gravity data represents nowadays major issues for the terrain correction computation. Classical methods such as prism or point masses approximations are indeed too slow while Fourier based techniques are usually too approximate for the required accuracy. In this work a new software, called Gravity Terrain Effects (GTE), developed to guarantee high accuracy and fast computation of terrain corrections is presented. GTE has been thought expressly for geophysical applications allowing the computation not only of the effect of topographic and bathymetric masses but also those due to sedimentary layers or to the Earth crust-mantle discontinuity (the so-called Moho). In the present contribution, after recalling the main classical algorithms for the computation of the terrain correction we summarize the basic theory of the software and its practical implementation. Some tests to prove its performances are also described showing GTE capability to compute high accurate terrain corrections in a very short time: results obtained for a real airborne survey with GTE ranges between few hours and few minutes, according to the GTE profile used, with differences with respect to both planar and spherical computations (performed by prism and tesseroid respectively) of the order of 0.02 mGal even when using fastest profiles