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Ever since its presence was reported in the brain, the nature and role of hydrogen sulfide (H2S) in the Central Nervous System (CNS) have changed. Consequently, H2S has been elected as the third gas transmitter, along with carbon monoxide and nitric oxide, and a number of studies have focused on its neuromodulatory and protectant functions in physiological conditions. The research on H2S has highlighted its many facets in the periphery and in the CNS, and its role as a double-faced compound, switching from protective to toxic depending on its concentration. In this review, we will focus on the bell-shaped nature of H2S as an angiogenic factor and as a molecule released by glial cells (mainly astrocytes) and non-neuronal cells acting on the surrounding environment (paracrine) or on the releasing cells themselves (autocrine). Finally, we will discuss its role in Amyotrophic Lateral Sclerosis, a paradigm of a neurodegenerative disease.

Prostate cancer (PCa) continues to be the second most common malignant tumour and the main cause of oncological death in men. Investigating endogenous volatile organic metabolites (VOMs) produced by various metabolic pathways is emerging as a novel, effective, and non-invasive source of information to establish the volatilomic biosignature of PCa. In this study, headspace solid-phase microextraction combined with gas chromatography-mass spectrometry (HS-SPME/GC-MS) was used to establish the urine volatilomic profile of PCa and identify VOMs that can discriminate between the two investigated groups. This non-invasive approach was applied to oncological patients (PCa group, n = 26) and cancer-free individuals (control group, n = 30), retrieving a total of 147 VOMs from various chemical families. This included terpenes, norisoprenoid, sesquiterpenes, phenolic, sulphur and furanic compounds, ketones, alcohols, esters, aldehydes, carboxylic acid, benzene and naphthalene derivatives, hydrocarbons, and heterocyclic hydrocarbons. The data matrix was subjected to multivariate analysis, namely partial least-squares discriminant analysis (PLS-DA). Accordingly, this analysis showed that the group under study presented different volatomic profiles and suggested potential PCa biomarkers. Nevertheless, a larger cohort of samples is required to boost the predictability and accuracy of the statistical models developed.

African Swine Fever (ASF) is an acute hemorrhagic fever affecting suids with high mortality and morbidity rate. The causal agent of ASF, the African Swine Fever Virus (ASFV), is an icosahedral virus of 200 nm diameter, composed of an outer envelope layer of host derivation and a linear 170-190 kb long dsDNA molecule. As of today, no efficient therapeutic intervention nor prophylactic measures exist to fight ASFV diffusion, underlining the importance of the early diagnosis and the need for efficient in-field screening of ASF. Recommended guidelines for the diagnosis of ASF are unpracticable in the desirable context of the rapid in-farm screening. In this view, the design of innovative diagnostics based on a panel of multiple ASFV epitopes would amend versatility and the analytical performances of the deliverable, ensuring high quality and accuracy standards worth of implementation in rapid in-field monitoring programs. Pursuing this view, we performed epitope prediction from the major AFSV structural proteins holding the potential to be targeted in innovative rapid diagnostic tests. Selected ASFV structural protein sequences were retrieved from data repositories and their tridimensional structure was computed. Linear and 3D protein structures were subjected to the prediction of the epitope sequences, that are likely to elicit antibody production, by independent bioinformatic tools, providing a list of candidate biomarkers whose batch employment held the potential suitability for the unbiased rapid in-field diagnosis and, in turn, might be implemented in screening programs, crowing the current monitoring and control campaigns that are currently running worldwide.

Volatile organic compounds (VOCs) are a differentiated class of molecules, continuously generated in the human body and released as products of metabolic pathways. Their concentrations vary depending on pathophysiological conditions. They are detectable in a wide variety of biological samples, such as exhaled breath, faeces, and urine. In particular, urine represents an easily accessible specimen widely used in clinics. The most used techniques for VOCs detections are expensive and time-consuming, thus not allowing for rapid clinical analysis. In this perspective, the aim of this study is a comprehensive characterisation of the urine volatilome by the development of an alternative rapid analytical method. Briefly, 115 urine samples are collected; sample treatment is not needed. VOCs are detected in the urine headspace using gas chromatography coupled to ion mobility spectrometry (GC-IMS) by an extremely fast analysis (10 min). The method is analytically validated; the analysis is sensitive and robust with results comparable to those reported with other techniques. Twenty-three molecules are identified, including ketones, aldehydes, alcohols, and sulphur compounds, whose concentration is altered in several pathological states such as cancer and metabolic disorders. Therefore, it opens new perspectives for fast diagnosis and screening, showing great potential for clinical applications.