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Abstract Background The pleiotropic pro-inflammatory cytokine Interleukin (IL)-18 has been proposed to play a role in schizophrenia, since elevated circulating levels of its protein and altered frequencies of genetic variants in its molecular system are reported in schizophrenic patients. Methods We analyzed 77 patients with schizophrenia diagnosis (SCZ) and 77 healthy control subjects (HC) for serum concentration of both IL-18 and its natural inhibitor, the IL-18 binding protein (IL-18BP). Results We confirmed that serum levels of total IL-18 are significantly increased in SCZ, as compared to HC. However, due to a highly significant increase in levels of circulating IL-18BP in SCZ, as compared to HC, the levels of free, bioactive IL-18 are not significantly different between the two groups. In addition, the relationships between the levels of IL-18 and its inhibitor, as well as between the two molecules and age appear dissimilar for SCZ and HC. In particular, the elevated levels of IL-18BP, likely a consequence of the body’s attempt to counteract the early prominent inflammation which characterizes schizophrenia, are maintained in earlier and later stages of the disease. However, the IL-18BP elevation appears ineffective to balance the IL-18 system in younger SCZ patients, while in older patients the levels of circulating bioactive IL-18 are comparable to those of HC, if not lower. Conclusions In conclusion, these findings indicate that the IL-18 system is perturbed in schizophrenia, supporting the idea that this pro-inflammatory cytokine might be part of a pathway of genetic and environmental components for vulnerability to the disease.

The Autism Spectrum Disorders in the European Union (ASDEU) survey investigated local services' use experiences of autistic adults, carers and professionals with interventions for autistic adults. The majority of the 697 participants experienced recommended considerations prior to deciding on intervention and during the intervention plan and implementation. Psychosocial interventions were the most commonly experienced interventions, while pharmacological interventions NOT recommended for core autistic symptoms were reported by fairly large proportions of participants. Family interventions were experienced slightly more commonly by carers than adults or professionals. Less than the 26% of autistic adult responders who had experienced challenging behaviors reported receiving an intervention to change them. These results provide insights for improving gaps in service provision of interventions among autistic adults.

Research providing an evidence-base for autistic adult services is sparse. The Autism Spectrum Disorders in the European Union (ASDEU) network implemented an on-line survey to determine gaps in autistic adult diagnostic evaluation and post-diagnostic support services. More than 55% in all groups experienced most of the recommended features for diagnostic evaluation for autistic adults. In contrast, < 2% of adults or carers, and < 21% of professionals experienced each of the recommended features for post-diagnostic support. In contrast to 61% of professionals, only about 30% of autistic adults and carers had knowledge of good local services models for autism diagnosis in adulthood. There are major differences between good practice guidelines for diagnostic and post-diagnostic care for autistic adults, and what is actually experienced by services users and professionals.

A number of studies have suggested that influenza vaccination can provide protection against COVID-19, but the underlying mechanisms that could explain this association are still unclear. In this study, the effect of the 2021/2022 seasonal influenza vaccination on the immune response to the booster dose of anti-SARS-CoV-2 vaccination was evaluated in a cohort of healthy individuals. A total of 113 participants were enrolled, 74 of whom had no prior COVID-19 diagnosis or significant comorbidities were considered for the analysis. Participants received the anti-influenza tetravalent vaccine and the booster dose of the anti-SARS-CoV-2 vaccine or the anti-SARS-CoV-2 vaccine alone. Blood was collected before and 4 weeks after each vaccination and 12 weeks after SARS-CoV-2 vaccination and analyzed for anti-flu and anti-spike-specific antibody titers and for in vitro influenza and SARS-CoV-2 neutralization capacity. Results indicated an increased reactivity in subjects who received both influenza and SARS-CoV-2 vaccinations compared to those who received only the SARS-CoV-2 vaccine, with sustained anti-spike antibody titers up to 12 weeks post-vaccination. Immune response to the influenza vaccine was evaluated, and individuals were stratified as high or low responders. High responders showed increased antibody titers against the SARS-CoV-2 vaccine both after 4 and 12 weeks post-vaccination. Conversely, individuals classified as low responders were less responsive to the SARS-CoV-2 vaccine. These data indicate that both external stimuli, such as influenza vaccination, and the host’s intrinsic ability to respond to stimuli play a role in the response to the vaccine.

This paper presents original findings on the heterogeneity of the mechanical properties of concrete of an early age, dependent on the evolution of the hydration reaction. The properties investigated are the compressive strength, the Young’s modulus, and the flexural tensile strength. To achieve this, we employed a testing apparatus in which the samples underwent curing in a chamber that followed the same temperature profile as an adiabatic calorimeter. This method enabled us to monitor the hydration progress across multiple samples. We used a function derived from the literature, with specific adaptations, to model the evolution of normalized properties in relation to hydration. Heterogeneity was quantified through the use of the dispersion coefficient. The key finding of this study is that the dispersion coefficient for the analyzed mechanical properties diminishes with the advancement of hydration, until reaching a specific threshold. Beyond this point, the impact of microcracking on the various properties becomes increasingly pronounced, varying according to the particular property being examined. Moreover, this paper presents initial functions designed to offer formulas that assist in modeling concrete within probabilistic numerical simulations from the early stages of its development.

The ARGO-USV (Unmanned Surface Vehicle for ARchaeological GeO-application) is a technological project involving a marine drone aimed at devising an innovative methodology for marine geological and geomorphological investigations in shallow areas, usually considered critical areas to be investigated, with the help of traditional vessels. The methodological approach proposed in this paper has been implemented according to a multimodal mapping technique involving the simultaneous and integrated use of both optical and geoacoustic sensors. This approach has been enriched by tools based on artificial intelligence (AI), specifically intended to be installed onboard the ARGO-USV, aimed at the automatic recognition of submerged targets and the physical characterization of the seabed. This technological project is composed of a main command and control system and a series of dedicated sub-systems successfully tested in different operational scenarios. The ARGO drone is capable of acquiring and storing a considerable amount of georeferenced data during surveys lasting a few hours. The transmission of all acquired data in broadcasting allows the cooperation of a multidisciplinary team of specialists able to analyze specific datasets in real time. These features, together with the use of deep-learning-based modules and special attention to green-compliant construction phases, are the particular aspects that make ARGO-USV a modern and innovative project, aiming to improve the knowledge of wide coastal areas while minimizing the impact on these environments. As a proof-of-concept, we present the extensive mapping and characterization of the seabed from a geoarchaeological survey of the underwater Roman harbor of Puteoli in the Gulf of Naples (Italy), demonstrating that deep learning techniques can work synergistically with seabed mapping methods.