1H-NMR-Based Metabolomics in Autism Spectrum Disorder and Pediatric Acute-Onset Neuropsychiatric Syndrome

We recently described a unique plasma metabolite profile in subjects with pediatric acute-onset neuropsychiatric syndrome (PANS), suggesting pathogenic models involving specific patterns of neurotransmission, neuroinflammation, and oxidative stress. Here, we extend the analysis to a group of patients with autism spectrum disorder (ASD), as a consensus has recently emerged around its immune-mediated pathophysiology with a widespread involvement of brain networks. This observational case-control study enrolled patients referred for PANS and ASD from June 2019 to May 2020, as well as neurotypical age and gender-matched control subjects. Thirty-four PANS outpatients, fifteen ASD outpatients, and twenty-five neurotypical subjects underwent physical and neuropsychiatric evaluations, alongside serum metabolomic analysis with 1H-NMR. In supervised models, the metabolomic profile of ASD was significantly different from controls (p = 0.0001), with skewed concentrations of asparagine, aspartate, betaine, glycine, lactate, glucose, and pyruvate. Metabolomic separation was also observed between PANS and ASD subjects (p = 0.02), with differences in the concentrations of arginine, aspartate, betaine, choline, creatine phosphate, glycine, pyruvate, and tryptophan. We confirmed a unique serum metabolomic profile of PANS compared with both ASD and neurotypical subjects, distinguishing PANS as a pathophysiological entity per se. Tryptophan and glycine appear as neuroinflammatory fingerprints of PANS and ASD, respectively. In particular, a reduction in glycine would primarily affect NMDA-R excitatory tone, overall impairing downstream glutamatergic, dopaminergic, and GABAergic transmissions. Nonetheless, we found metabolomic similarities between PANS and ASD that suggest a putative role of N-methyl-D-aspartate receptor (NMDA-R) dysfunction in both disorders. Metabolomics-based approaches could contribute to the identification of novel ASD and PANS biomarkers

Intrinsic time resolution of 3D-trench silicon pixels for charged particle detection

In the last years, high-resolution time tagging has emerged as the tool to tackle the problem of high-track density in the detectors of the next generation of experiments at particle colliders. Time resolutions below 50ps and event average repetition rates of tens of MHz on sensor pixels having a pitch of 50$\mu$m are typical minimum requirements. This poses an important scientific and technological challenge on the development of particle sensors and processing electronics. The TIMESPOT initiative (which stands for TIME and SPace real-time Operating Tracker) aims at the development of a full prototype detection system suitable for the particle trackers of the next-to-come particle physics experiments. This paper describes the results obtained on the first batch of TIMESPOT silicon sensors, based on a novel 3D MEMS (micro electro-mechanical systems) design. Following this approach, the performance of other ongoing silicon sensor developments has been matched and overcome, while using a technology which is known to be robust against radiation degradation. A time resolution of the order of 20ps has been measured at room temperature suggesting also possible improvements after further optimisations of the front-end electronics processing stage.Comment: This version was accepted to be published on JINST on 21/07/202