The Analgesic Effect of Oxytocin in Humans: A Double-Blind, Placebo-Controlled Cross-Over Study Using Laser-Evoked Potentials

Oxytocin is a neuropeptide regulating social‐affiliative and reproductive behaviour in mammals. Despite robust preclinical evidence for the antinociceptive effects and mechanisms of action of exogenous oxytocin, human studies have produced mixed results regarding the analgesic role of oxytocin and are yet to show a specific modulation of neural processes involved in pain perception. In the present study, we investigated the analgesic effects of 40 IU of intranasal oxytocin in 13 healthy male volunteers using a double‐blind, placebo‐controlled, cross‐over design and brief radiant heat pulses generated by an infrared laser that selectively activate Aδ‐ and C‐fibre nerve endings in the epidermis, at the same time as recording the ensuing laser‐evoked potentials (LEPs). We predicted that oxytocin would reduce subjective pain ratings and attenuate the amplitude of the N1, N2 and P2 components. We observed that oxytocin attenuated perceived pain intensity and the local peak amplitude of the N1 and N2 (but not of P2) LEPs, and increased the latency of the N2 component. Importantly, for the first time, the present study reports an association between the analgesic effect of oxytocin (reduction in subjective pain ratings) and the oxytocin‐induced modulation of cortical activity after noxious stimulation (attenuation of the N2 LEP). These effects indicate that oxytocin modulates neural processes contributing to pain perception. The present study reports preliminary evidence that is consistent with electrophysiological studies in rodents showing that oxytocin specifically modulates Aδ/C‐fibre nociceptive afferent signalling at the spinal level and provides further specificity to evidence obtained in humans indicating that oxytocin may be modulating pain experience by modulating activity in the cortical areas involved in pain processing

Semi-Supervised Fine-Tuning for Deep Learning Models in Remote Sensing Applications

A combinatory approach of two well-known fields: deep learning and semi supervised learning is presented, to tackle the land cover identification problem. The proposed methodology demonstrates the impact on the performance of deep learning models, when SSL approaches are used as performance functions during training. Obtained results, at pixel level segmentation tasks over orthoimages, suggest that SSL enhanced loss functions can be beneficial in models' performance

Validation of the Mind Excessively Wandering Scale and the Relationship of Mind Wandering to Impairment in Adult ADHD.

OBJECTIVE: This study investigates excessive mind wandering (MW) in adult ADHD using a new scale: the Mind Excessively Wandering Scale (MEWS). METHOD: Data from two studies of adult ADHD was used in assessing the psychometric properties of the MEWS. Case-control differences in MW, the association with ADHD symptoms, and the contribution to functional impairment were investigated. RESULTS: The MEWS functioned well as a brief measure of excessive MW in adult ADHD, showing good internal consistency (α > .9), and high sensitivity (.9) and specificity (.9) for the ADHD diagnosis, comparable with that of existing ADHD symptom rating scales. Elevated levels of MW were found in adults with ADHD, which contributed to impairment independently of core ADHD symptom dimensions. CONCLUSION: Findings suggest excessive MW is a common co-occurring feature of adult ADHD that has specific implications for the functional impairments experienced. The MEWS has potential utility as a screening tool in clinical practice to assist diagnostic assessment

A Gas Leak Rate Measurement System for the ATLAS MUON BIS-Monitored Drift Tubes

A low-cost, reliable and precise system developed for the gas leak rate measurement of the BIS-Monitored Drift Tubes (MDTs) for the ATLAS Muon Spectrometer is presented. In order to meet the BIS-MDT mass production rate, a total number of 100 tubes are tested simultaneously in this setup. The pressure drop of each one of the MDT is measured, within a typical time interval of 48 hours, via a differential manometer comparing with the pressure of a gas tight reference tube. The precision of the method implemented is based on the system temperature homogeneity, with accuracy of ÄT = 0.3 oC. For this reason, two thermally isolated boxes are used testing 50 tubes each of them, to achieve high degree of temperature uniformity and stability. After measuring several thousands of the MDTs, the developed system is confirmed to be appropriate within the specifications for testing the MDTs during the mass production

Immune signatures and disorder-specific patterns in a cross-disorder gene expression analysis

BACKGROUND: Recent studies point to overlap between neuropsychiatric disorders in symptomatology and genetic aetiology. AIMS: To systematically investigate genomics overlap between childhood and adult attention-deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD) and major depressive disorder (MDD). METHOD: Analysis of whole-genome blood gene expression and genetic risk scores of 318 individuals. Participants included individuals affected with adult ADHD (n = 93), childhood ADHD (n = 17), MDD (n = 63), ASD (n = 51), childhood dual diagnosis of ADHD-ASD (n = 16) and healthy controls (n = 78). RESULTS: Weighted gene co-expression analysis results reveal disorder-specific signatures for childhood ADHD and MDD, and also highlight two immune-related gene co-expression modules correlating inversely with MDD and adult ADHD disease status. We find no significant relationship between polygenic risk scores and gene expression signatures. CONCLUSIONS: Our results reveal disorder overlap and specificity at the genetic and gene expression level. They suggest new pathways contributing to distinct pathophysiology in psychiatric disorders and shed light on potential shared genomic risk factors

System Test of the ATLAS Muon Spectrometer in the H8 Beam at the CERN SPS

An extensive system test of the ATLAS muon spectrometer has been performed in the H8 beam line at the CERN SPS during the last four years. This spectrometer will use pressurized Monitored Drift Tube (MDT) chambers and Cathode Strip Chambers (CSC) for precision tracking, Resistive Plate Chambers (RPCs) for triggering in the barrel and Thin Gap Chambers (TGCs) for triggering in the end-cap region. The test set-up emulates one projective tower of the barrel (six MDT chambers and six RPCs) and one end-cap octant (six MDT chambers, A CSC and three TGCs). The barrel and end-cap stands have also been equipped with optical alignment systems, aiming at a relative positioning of the precision chambers in each tower to 30-40 micrometers. In addition to the performance of the detectors and the alignment scheme, many other systems aspects of the ATLAS muon spectrometer have been tested and validated with this setup, such as the mechanical detector integration and installation, the detector control system, the data acquisition, high level trigger software and off-line event reconstruction. Measurements with muon energies ranging from 20 to 300 GeV have allowed measuring the trigger and tracking performance of this set-up, in a configuration very similar to the final spectrometer. A special bunched muon beam with 25 ns bunch spacing, emulating the LHC bunch structure, has been used to study the timing resolution and bunch identification performance of the trigger chambers. The ATLAS first-level trigger chain has been operated with muon trigger signals for the first time