Serotonin syndrome:pathophysiology, clinical features, management, and potential future directions

Serotonin syndrome (SS) (also referred to as serotonin toxicity) is a potentially life-threatening drug-induced toxidrome associated with increased serotonergic activity in both the peripheral (PNS) and central nervous systems (CNS). It is characterised by a dose-relevant spectrum of clinical findings related to the level of free serotonin (5-hydroxytryptamine [5-HT]), or 5-HT receptor activation (predominantly the 5-HT1A and 5-HT2A subtypes), which include neuromuscular abnormalities, autonomic hyperactivity, and mental state changes. Severe SS is only usually precipitated by the simultaneous initiation of 2 or more serotonergic drugs, but the syndrome can also occur after the initiation of a single serotonergic drug in a susceptible individual, the addition of a second or third agent to long-standing doses of a maintenance serotonergic drug, or after an overdose. The combination of a monoamine oxidase inhibitor (MAOI), in particular MAO-A inhibitors that preferentially inhibit the metabolism of 5-HT, with serotonergic drugs is especially dangerous, and may lead to the most severe form of the syndrome, and occasionally death. This review describes our current understanding of the pathophysiology, clinical presentation and management of SS, and summarises some of the drugs and interactions that may precipitate the condition. We also discuss the newer novel psychoactive substances (NPSs), a growing public health concern due to their increased availability and use, and their potential risk to evoke the syndrome. Finally, we discuss whether the inhibition of tryptophan hydroxylase (TPH), in particular the neuronal isoform (TPH2), may provide an opportunity to pharmacologically target central 5-HT synthesis, and so develop new treatments for severe, life-threatening SS

Progressive severe lung injury by zinc oxide nanoparticles; the role of Zn2+ dissolution inside lysosomes

Background: Large production volumes of zinc oxide nanoparticles (ZnONP) might be anticipated to pose risks, of accidental inhalation in occupational and even in consumer settings. Herein, we further investigated the pathological changes induced by ZnONP and their possible mechanism of action.Methods: Two doses of ZnONP (50 and 150 cm(2)/rat) were intratracheally instilled into the lungs of rats with assessments made at 24 h, 1 wk, and 4 wks after instillation to evaluate dose- and time-course responses. Assessments included bronchoalveolar lavage (BAL) fluid analysis, histological analysis, transmission electron microscopy, and IgE and IgA measurement in the serum and BAL fluid. To evaluate the mechanism, alternative ZnONP, ZnONP-free bronchoalveolar lavage exudate, and dissolved Zn2+ (92.5 mu g/rat) were also instilled to rats. Acridine orange staining was utilized in macrophages in culture to evaluate the lysosomal membrane destabilization by NP.Results: ZnONP induced eosinophilia, proliferation of airway epithelial cells, goblet cell hyperplasia, and pulmonary fibrosis. Bronchocentric interstitial pulmonary fibrosis at the chronic phase was associated with increased myofibroblast accumulation and transforming growth factor-beta positivity. Serum IgE levels were up-regulated by ZnONP along with the eosinophilia whilst serum IgA levels were down-regulated by ZnONP. ZnONP are rapidly dissolved under acidic conditions (pH 4.5) whilst they remained intact around neutrality (pH 7.4). The instillation of dissolved Zn2+ into rat lungs showed similar pathologies (eg., eosinophilia, bronchocentric interstitial fibrosis) as were elicited by ZnONP. Lysosomal stability was decreased and cell death resulted following treatment of macrophages with ZnONP in vitro.Conclusions: We hypothesise that rapid, pH-dependent dissolution of ZnONP inside of phagosomes is the main cause of ZnONP-induced diverse progressive severe lung injuries

Multimodal MRI can identify perfusion and metabolic changes in the invasive margin of glioblastomas.

PURPOSE: To use perfusion and magnetic resonance (MR) spectroscopy to compare the diffusion tensor imaging (DTI)-defined invasive and noninvasive regions. Invasion of normal brain is a cardinal feature of glioblastomas (GBM) and a major cause of treatment failure. DTI can identify invasive regions. MATERIALS AND METHODS: In all, 50 GBM patients were imaged preoperatively at 3T with anatomic sequences, DTI, dynamic susceptibility perfusion MR (DSCI), and multivoxel spectroscopy. The DTI and DSCI data were coregistered to the spectroscopy data and regions of interest (ROIs) were made in the invasive (determined by DTI), noninvasive regions, and normal brain. Values of relative cerebral blood volume (rCBV), N-acetyl aspartate (NAA), myoinositol (mI), total choline (Cho), and glutamate + glutamine (Glx) normalized to creatine (Cr) and Cho/NAA were measured at each ROI. RESULTS: Invasive regions showed significant increases in rCBV, suggesting angiogenesis (invasive rCBV 1.64 [95% confidence interval, CI: 1.5-1.76] vs. noninvasive 1.14 [1.09-1.18]; P < 0.001), Cho/Cr (invasive 0.42 [0.38-0.46] vs. noninvasive 0.35 [0.31-0.38]; P = 0.02) and Cho/NAA (invasive 0.54 [0.41-0.68] vs. noninvasive 0.37 [0.29-0.45]; P = < 0.03), suggesting proliferation, and Glx/Cr (invasive 1.54 [1.27-1.82] vs. noninvasive 1.3 [1.13-1.47]; P = 0.028), suggesting glutamate release; and a significantly reduced NAA/Cr (invasive 0.95 [0.85-1.05] vs. noninvasive 1.19 [1.06-1.31]; P = 0.008). The mI/Cr was not different between the three ROIs (invasive 1.2 [0.99-1.41] vs. noninvasive 1.3 [1.14-1.46]; P = 0.68). In the noninvasive regions, the values were not different from normal brain. CONCLUSION: Combining DTI to identify the invasive region with perfusion and spectroscopy, we can identify changes in invasive regions not seen in noninvasive regions.This study was funded from a National Institutes of Health Research Clinician Scientist FellowshipThis is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1002/jmri.2499

The temporal event-based model: Learning event timelines in progressive diseases

Timelines of events, such as symptom appearance or a change in biomarker value, provide powerful signatures that characterise progressive diseases. Understanding and predicting the timing of events is important for clinical trials targeting individuals early in the disease course when putative treatments are likely to have the strongest effect. However, previous models of disease progression cannot estimate the time between events and provide only an ordering in which they change. Here, we introduce the temporal event-based model (TEBM), a new probabilistic model for inferring timelines of biomarker events from sparse and irregularly sampled datasets. We demonstrate the power of the TEBM in two neurodegenerative conditions: Alzheimer's disease (AD) and Huntington's disease (HD). In both diseases, the TEBM not only recapitulates current understanding of event orderings but also provides unique new ranges of timescales between consecutive events. We reproduce and validate these findings using external datasets in both diseases. We also demonstrate that the TEBM improves over current models; provides unique stratification capabilities; and enriches simulated clinical trials to achieve a power of 80% with less than half the cohort size compared with random selection. The application of the TEBM naturally extends to a wide range of progressive conditions

Topiramate is more effective than acetazolamide at lowering intracranial pressure

BACKGROUND The management of idiopathic intracranial hypertension focuses on reducing intracranial pressure to preserve vision and reduce headaches. There is sparse evidence to support the use of some of the drugs commonly used to manage idiopathic intracranial hypertension, therefore we propose to evaluate the efficacy of these drugs at lowering intracranial pressure in healthy rats. METHODS We measured intracranial pressure in female rats before and after subcutaneous administration of acetazolamide, topiramate, furosemide, amiloride and octreotide at clinical doses (equivalent to a single human dose) and high doses (equivalent to a human daily dose). In addition, we measured intracranial pressure after oral administration of acetazolamide and topiramate. RESULTS At clinical and high doses, subcutaneous administration of topiramate lowered intracranial pressure by 32% ( p = 0.0009) and 21% ( p = 0.015) respectively. There was no significant reduction in intracranial pressure noted with acetazolamide, furosemide, amiloride or octreotide at any dose. Oral administration of topiramate significantly lowered intracranial pressure by 22% ( p = 0.018), compared to 5% reduction with acetazolamide ( p = >0.999). CONCLUSION Our in vivo studies demonstrated that both subcutaneous and oral administration of topiramate significantly lowers intracranial pressure. Other drugs tested, including acetazolamide, did not significantly reduce intracranial pressure. Future clinical trials evaluating the efficacy and side effects of topiramate in idiopathic intracranial hypertension patients would be of interest

Uncovering spatiotemporal patterns of atrophy in progressive supranuclear palsy using unsupervised machine learning

To better understand the pathological and phenotypic heterogeneity of progressive supranuclear palsy and the links between the two, we applied a novel unsupervised machine learning algorithm (Subtype and Stage Inference) to the largest MRI data set to date of people with clinically diagnosed progressive supranuclear palsy (including progressive supranuclear palsy-Richardson and variant progressive supranuclear palsy syndromes). Our cohort is comprised of 426 progressive supranuclear palsy cases, of which 367 had at least one follow-up scan, and 290 controls. Of the progressive supranuclear palsy cases, 357 were clinically diagnosed with progressive supranuclear palsy-Richardson, 52 with a progressive supranuclear palsy-cortical variant (progressive supranuclear palsy-frontal, progressive supranuclear palsy-speech/language, or progressive supranuclear palsy-corticobasal), and 17 with a progressive supranuclear palsy-subcortical variant (progressive supranuclear palsy-parkinsonism or progressive supranuclear palsy-progressive gait freezing). Subtype and Stage Inference was applied to volumetric MRI features extracted from baseline structural (T1-weighted) MRI scans and then used to subtype and stage follow-up scans. The subtypes and stages at follow-up were used to validate the longitudinal consistency of subtype and stage assignments. We further compared the clinical phenotypes of each subtype to gain insight into the relationship between progressive supranuclear palsy pathology, atrophy patterns, and clinical presentation. The data supported two subtypes, each with a distinct progression of atrophy: a 'subcortical' subtype, in which early atrophy was most prominent in the brainstem, ventral diencephalon, superior cerebellar peduncles, and the dentate nucleus, and a 'cortical' subtype, in which there was early atrophy in the frontal lobes and the insula alongside brainstem atrophy. There was a strong association between clinical diagnosis and the Subtype and Stage Inference subtype with 82% of progressive supranuclear palsy-subcortical cases and 81% of progressive supranuclear palsy-Richardson cases assigned to the subcortical subtype and 82% of progressive supranuclear palsy-cortical cases assigned to the cortical subtype. The increasing stage was associated with worsening clinical scores, whilst the 'subcortical' subtype was associated with worse clinical severity scores compared to the 'cortical subtype' (progressive supranuclear palsy rating scale and Unified Parkinson's Disease Rating Scale). Validation experiments showed that subtype assignment was longitudinally stable (95% of scans were assigned to the same subtype at follow-up) and individual staging was longitudinally consistent with 90% remaining at the same stage or progressing to a later stage at follow-up. In summary, we applied Subtype and Stage Inference to structural MRI data and empirically identified two distinct subtypes of spatiotemporal atrophy in progressive supranuclear palsy. These image-based subtypes were differentially enriched for progressive supranuclear palsy clinical syndromes and showed different clinical characteristics. Being able to accurately subtype and stage progressive supranuclear palsy patients at baseline has important implications for screening patients on entry to clinical trials, as well as tracking disease progression

The management and outcome for patients with chronic subdural hematoma: a prospective, multicenter, observational cohort study in the United Kingdom

Symptomatic chronic subdural hematoma (CSDH) will become an increasingly common presentation in neurosurgical practice as the population ages, but quality evidence is still lacking to guide the optimal management for these patients. The British Neurosurgical Trainee Research Collaborative (BNTRC) was established by neurosurgical trainees in 2012 to improve research by combining the efforts of trainees in each of the United Kingdom (UK) and Ireland's neurosurgical units (NSUs). The authors present the first study by the BNTRC that describes current management and outcomes for patients with CSDH throughout the UK and Ireland. This provides a resource both for current clinical practice and future clinical research on CSDH

Author Correction: The IPDGC/GP2 Hackathon - an open science event for training in data science, genomics, and collaboration using Parkinson’s disease data

Correction to: npj Parkinson’s Disease https://doi.org/10.1038/s41531-023-00472-6, published online 04 March 2023// In this article the affiliation details for Alastair J Noyce, Jonggeol Jeff Kim, Isabelle Francesca Foote, Sumit Dey were incorrectly given as ‘Department of Genetics and Genomic Sciences and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount, Hess Center for Science and Medicine, New York, NY 10029, USA,’ but should have been ‘Preventive Neurology Unit, Wolfson Institute of Population Health, Queen Mary University of London, London, UK’.// The affiliation details for Prabhjyot Saini were incorrectly given as ‘Preventive Neurology Unit, Wolfson Institute of Population Health, Queen Mary University of London, London, UK’ but should have been ‘The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, QC, Canada’. The original article has been corrected

The IPDGC/GP2 Hackathon - an open science event for training in data science, genomics, and collaboration using Parkinson’s disease data

Open science and collaboration are necessary to facilitate the advancement of Parkinson's disease (PD) research. Hackathons are collaborative events that bring together people with different skill sets and backgrounds to generate resources and creative solutions to problems. These events can be used as training and networking opportunities, thus we coordinated a virtual 3-day hackathon event, during which 49 early-career scientists from 12 countries built tools and pipelines with a focus on PD. Resources were created with the goal of helping scientists accelerate their own research by having access to the necessary code and tools. Each team was allocated one of nine different projects, each with a different goal. These included developing post-genome-wide association studies (GWAS) analysis pipelines, downstream analysis of genetic variation pipelines, and various visualization tools. Hackathons are a valuable approach to inspire creative thinking, supplement training in data science, and foster collaborative scientific relationships, which are foundational practices for early-career researchers. The resources generated can be used to accelerate research on the genetics of PD