Advancing education in interventional psychiatry: scoping review of simulation training and the future of virtual reality-based learning

ObjectivesInterventional psychiatric procedures such as electroconvulsive therapy (ECT) and repetitive transcranial magnetic stimulation (rTMS) have become increasingly important therapeutic options for managing severe or treatment-resistant mental illnesses. However, research suggests that gaps in training students in these techniques represent a rate-limiting step for their further dissemination and accessibility for the public. Studies have shown that the majority of psychiatry residents lack necessary competency and self-confidence in performing these treatments. Simulation based training has served as a gold standard for training procedural skills in medicine. Simulation-based training environments, particularly immersive reality technology (e.g., virtual reality [VR]), represent a promising novel avenue for trainees to develop the necessary skills for delivering these treatments. This scoping review discusses the current training in interventional psychiatry and how simulation-based training, specifically VR, can improve pedagogy in this area.MethodsIn this scoping review, a literature search was conducted on the PubMed database using specific search terms such as “simulat*”, “training”, “ECT”, “TMS”, “neuromodulation”, and “interventional psychiatry”. The search was limited to studies with language in English from 1980 to 2023.ResultsThe initial search yielded 2094 articles, of which 4 evaluated the effectiveness of simulation approaches for ECT and were included in this review. No published studies were identified regarding VR-based education in ECT or rTMS.ConclusionsThis scoping review provides an overview of the current landscape of pedagogical methods in interventional psychiatry and highlights the identified gaps in both the existing literature and the potential application of simulation-based environments, including VR, within this field. Considering the ongoing shift in medical education towards competency-based training, this review discusses the needs and benefits of VR-based simulators as an avenue to enhance competency in interventional psychiatry. Leveraging existing experience in the use of VR-based simulators in procedural skill acquisition in surgery and anesthesia, as well as recommendations on how to translate this approach to clinical training in psychiatry, are also discussed

Resting state cortico-thalamic-striatal connectivity predicts pesponse to dorsomedial prefrontal rTMS in major depressive disorder

Despite its high toll on society, there has been little recent improvement in treatment efficacy for Major Depressive Disorder (MDD). The identification of biological markers of successful treatment response may allow for more personalized and effective treatment. Here we investigate whether resting state functional connectivity predicted response to treatment with rapid transcranial magnetic stimulation (rTMS) to dorsomedial prefrontal cortex (dmPFC). Twenty five individuals with treatment-refractory MDD underwent a 4-week course of dmPFC-rTMS. Before and after treatment, subjects received resting state functional MRI scans and assessments of depressive symptoms using the Hamilton Depresssion Rating Scale (HAMD17). We found that higher baseline cortico-cortical connectivity (dmPFC-subgenual cingulate and subgenual cingulate to dorsolateral PFC) and lower cortico-thalamic, cortico-striatal and cortico-limbic connectivity were associated with better treatment outcomes. We also investigated how changes in connectivity over the course of treatment related to improvements in HAMD17 scores. We found that successful treatment was associated with increased dmPFC-thalamic connectivity and decreased sgACC-caudate connectivity, Our findings provide insight into which individuals might respond to rTMS treatment and the mechanisms through which these treatments work

A Fast EEG Forecasting Algorithm for Phase-Locked Transcranial Electrical Stimulation of the Human Brain

A growing body of research suggests that non-invasive electrical brain stimulation can more effectively modulate neural activity when phase-locked to the underlying brain rhythms. Transcranial alternating current stimulation (tACS) can potentially stimulate the brain in-phase to its natural oscillations as recorded by electroencephalography (EEG), but matching these oscillations is a challenging problem due to the complex and time-varying nature of the EEG signals. Here we address this challenge by developing and testing a novel approach intended to deliver tACS phase-locked to the activity of the underlying brain region in real-time. This novel approach extracts phase and frequency from a segment of EEG, then forecasts the signal to control the stimulation. A careful tuning of the EEG segment length and prediction horizon is required and has been investigated here for different EEG frequency bands. The algorithm was tested on EEG data from 5 healthy volunteers. Algorithm performance was quantified in terms of phase-locking values across a variety of EEG frequency bands. Phase-locking performance was found to be consistent across individuals and recording locations. With current parameters, the algorithm performs best when tracking oscillations in the alpha band (8–13 Hz), with a phase-locking value of 0.77 ± 0.08. Performance was maximized when the frequency band of interest had a dominant frequency that was stable over time. The algorithm performs faster, and provides better phase-locked stimulation, compared to other recently published algorithms devised for this purpose. The algorithm is suitable for use in future studies of phase-locked tACS in preclinical and clinical applications

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Enabling planetary science across light-years. Ariel Definition Study Report

Ariel, the Atmospheric Remote-sensing Infrared Exoplanet Large-survey, was adopted as the fourth medium-class mission in ESA's Cosmic Vision programme to be launched in 2029. During its 4-year mission, Ariel will study what exoplanets are made of, how they formed and how they evolve, by surveying a diverse sample of about 1000 extrasolar planets, simultaneously in visible and infrared wavelengths. It is the first mission dedicated to measuring the chemical composition and thermal structures of hundreds of transiting exoplanets, enabling planetary science far beyond the boundaries of the Solar System. The payload consists of an off-axis Cassegrain telescope (primary mirror 1100 mm x 730 mm ellipse) and two separate instruments (FGS and AIRS) covering simultaneously 0.5-7.8 micron spectral range. The satellite is best placed into an L2 orbit to maximise the thermal stability and the field of regard. The payload module is passively cooled via a series of V-Groove radiators; the detectors for the AIRS are the only items that require active cooling via an active Ne JT cooler. The Ariel payload is developed by a consortium of more than 50 institutes from 16 ESA countries, which include the UK, France, Italy, Belgium, Poland, Spain, Austria, Denmark, Ireland, Portugal, Czech Republic, Hungary, the Netherlands, Sweden, Norway, Estonia, and a NASA contribution

Review of influenza-associated pulmonary aspergillosis in ICU patients and proposal for a case definition: an expert opinion

Purpose: Invasive pulmonary aspergillosis is increasingly reported in patients with influenza admitted to the intensive care unit (ICU). Classification of patients with influenza-associated pulmonary aspergillosis (IAPA) using the current definitions for invasive fungal diseases has proven difficult, and our aim was to develop case definitions for IAPA that can facilitate clinical studies. Methods: A group of 29 international experts reviewed current insights into the epidemiology, diagnosis and management of IAPA and proposed a case definition of IAPA through a process of informal consensus. Results: Since IAPA may develop in a wide range of hosts, an entry criterion was proposed and not host factors. The entry criterion was defined as a patient requiring ICU admission for respiratory distress with a positive influenza test temporally related to ICU admission. In addition, proven IAPA required histological evidence of invasive septate hyphae and mycological evidence for Aspergillus. Probable IAPA required the detection of galactomannan or positive Aspergillus culture in bronchoalveolar lavage (BAL) or serum with pulmonary infiltrates or a positive culture in upper respiratory samples with bronchoscopic evidence for tracheobronchitis or cavitating pulmonary infiltrates of recent onset. The IAPA case definitions may be useful to classify patients with COVID-19-associated pulmonary aspergillosis (CAPA), while awaiting further studies that provide more insight into the interaction between Aspergillus and the SARS-CoV-2-infected lung. Conclusion: A consensus case definition of IAPA is proposed, which will facilitate research into the epidemiology, diagnosis and management of this emerging acute and severe Aspergillus disease, and may be of use to study CAPA

Frameworks and tools for risk assessment of manufactured nanomaterials

Commercialization of nanotechnologies entails a regulatory requirement for understanding their environmental, health and safety (EHS) risks. Today we face challenges to assess these risks, which emerge from uncertainties around the interactions of manufactured nanomaterials (MNs) with humans and the environment. In order to reduce these uncertainties, it is necessary to generate sound scientific data on hazard and exposure by means of relevant frameworks and tools. The development of such approaches to facilitate the risk assessment (RA) of MNs has become a dynamic area of research. The aim of this paper was to review and critically analyse these approaches against a set of relevant criteria. The analysis concluded that none of the reviewed frameworks were able to fulfill all evaluation criteria. Many of the existing modelling tools are designed to provide screening-level assessments rather than to support regulatory RA and risk management. Nevertheless, there is a tendency towards developing more quantitative, higher-tier models, capable of incorporating uncertainty into their analyses. There is also a trend towards developing validated experimental protocols for material identification and hazard testing, reproducible across laboratories. These tools could enable a shift from a costly case-by-case RA of MNs towards a targeted, flexible and efficient process, based on grouping and read-across strategies and compliant with the 3R (Replacement, Reduction, Refinement) principles. In order to facilitate this process, it is important to transform the current efforts on developing databases and computational models into creating an integrated data and tools infrastructure to support the risk assessment and management of MNs.Commercialization of nanotechnologies entails a regulatory requirement for understanding their environmental, health and safety (EHS) risks. Today we face challenges to assess these risks, which emerge from uncertainties around the interactions of manufactured nanomaterials (MNs) with humans and the environment. In order to reduce these uncertainties, it is necessary to generate sound scientific data on hazard and exposure by means of relevant frameworks and tools. The development of such approaches to facilitate the risk assessment (RA) of MNs has become a dynamic area of research. The aim of this paper was to review and critically analyse these approaches against a set of relevant criteria. The analysis concluded that none of the reviewed frameworks were able to fulfill all evaluation criteria. Many of the existing modelling tools are designed to provide screening level assessments rather than to support regulatory RA and risk management Nevertheless, there is a tendency towards developing more quantitative, higher-tier models, capable of incorporating uncertainty into their analyses. There is also a trend towards developing validated experimental protocols for material identification and hazard testing, reproducible across laboratories. These tools could enable a shift from a costly case-by-case RA of MNs towards a targeted, flexible and efficient process, based on grouping and read-across strategies and compliant with the 3R (Replacement, Reduction, Refinement) principles. In order to facilitate this process, it is important to transform the current efforts on developing databases and computational models into creating an integrated data and tools infrastructure to support the risk assessment and management of MNs. (C) 2016 Elsevier Ltd. All rights reserved