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Mutant huntingtin induces neuronal apoptosis via derepressing the non-canonical poly(A) polymerase PAPD5.
MicroRNAs (miRNAs) are small non-coding RNAs that play crucial roles in post-transcriptional gene regulation. Poly(A) RNA polymerase D5 (PAPD5) catalyzes the addition of adenosine to the 3' end of miRNAs. In this study, we demonstrate that the Yin Yang 1 protein, a transcriptional repressor of PAPD5, is recruited to both RNA foci and protein aggregates, resulting in an upregulation of PAPD5 expression in Huntington's disease (HD). Additionally, we identify a subset of PAPD5-regulated miRNAs with increased adenylation and reduced expression in our disease model. We focus on miR-7-5p and find that its reduction causes the activation of the TAB2-mediated TAK1-MKK4-JNK pro-apoptotic pathway. This pathway is also activated in induced pluripotent stem cell-derived striatal neurons and post-mortem striatal tissues isolated from HD patients. In addition, we discover that a small molecule PAPD5 inhibitor, BCH001, can mitigate cell death and neurodegeneration in our disease models. This study highlights the importance of PAPD5-mediated miRNA dysfunction in HD pathogenesis and suggests a potential therapeutic direction for the disease.
Detection of formal thought disorders in child and adolescent psychosis using machine learning and neuropsychometric data
IntroductionFormal Thought Disorder (FTD) is a significant clinical feature of early-onset psychosis, often associated with poorer outcomes. Current diagnostic methods rely on clinical assessment, which can be subjective and time-consuming. This study aimed to investigate the potential of neuropsychological tests and machine learning to differentiate individuals with and without FTD.MethodsA cohort of 27 young people with early-onset psychosis was included. Participants underwent neuropsychological assessment using the Iowa Gambling Task (IGT) and Simple Reaction Time (SRT) tasks. A range of machine learning models (Logistic Regression (LR), Support Vector Machines (SVM), Random Forest (RF) and eXtreme Gradient Boosting (XGBoost)) were employed to classify participants into FTD-positive and FTD-negative groups based on these neuropsychological measures and their antipsychotic regimen (medication load in chlorpromazine equivalents).ResultsThe best performing machine learning model was LR with mean +/- standard deviation of cross validation Receiver Operating Characteristic Area Under Curve (ROC AUC) score of 0.850 (+/- 0.133), indicating moderate-to-good discriminatory performance. Key features contributing to the model’s accuracy included IGT card selections, SRT reaction time (most notably standard deviation) and chlorpromazine equivalent milligrams. The model correctly classified 24 out of 27 participants.DiscussionThis study demonstrates the feasibility of using neuropsychological tests and machine learning to identify FTD in early-onset psychosis. Early identification of FTD may facilitate targeted interventions and improve clinical outcomes. Further research is needed to validate these findings in larger, more diverse populations and to explore the underlying neurocognitive mechanisms.
Diagnosis and Management of Multifocal Motor Neuropathy in the United Kingdom: A Multicentre Survey
ABSTRACTBackgroundWe conducted a survey to determine the current diagnosis and treatment of multifocal motor neuropathy (MMN) in the United Kingdom.MethodsDemographic, diagnostic and treatment data were collected at nine UK neuroscience centres.ResultsNinety‐five subjects were included. Mean age at diagnosis was 49.9 years (SD: 11.4). Males were more commonly affected (ratio: 1.9:1). Diagnostic delay was > 1 year from the time of first neurological assessment, in > 50% of subjects. Applying modified EFNS/PNS 2010 criteria, 69/95 (72.6%) had definite MMN, 10/95 (10.5%) had probable MMN, 15/95 (15.8%) had possible MMN, through treatment responsiveness in 9/15 (60%) and 1/95 (1.1%) did not meet criteria. Cerebrospinal fluid examination, anti‐GM1 antibody testing and brachial plexus magnetic resonance imaging were non‐contributory. Immunoglobulin response was reported in 90/92 subjects (97.8%), and 84/90 (93.3%) remained on treatment after a mean of 9.4 years, at a mean dose of 26.2 g/week (range: 4–114). Mean long‐term immunoglobulin dose was 30%–60% higher than reported in neighbouring countries. Contrasting with previous reports of frequent loss of immunoglobulin response and functional decline, our physician‐assessed long‐term outcome was favourable (stable or improving) in 74/84 (88.1%) treated subjects.InterpretationMMN diagnosis and treatment in the United Kingdom are comparable to that of neighbouring countries and follow existing guidelines. Diagnostic delay after the first neurological assessment is considerable. Electrophysiology shows at least one definite/probable conduction block in nearly 90% of cases. The mean long‐term immunoglobulin dose is higher in the United Kingdom than reported elsewhere, although highly variable. Whether higher doses of immunoglobulin may improve long‐term outcomes requires further study.
The ERGtools2 package: a toolset for processing and analysing visual electrophysiology data.
PURPOSE: To introduce ERGtools2, an open-source R package for processing, analysing and long-term storing visual electrophysiology data. METHODS: A dataset comprising Electroretinogram (ERG) recordings of C57Bl/6J mice, subjected to standard ISCEV stimuli, was used to present the functionality of ERGtools2. ERGtools2 stores and organizes all recordings, metadata, and measurement information from an individual examination in a single object, maintaining raw data throughout the analysis process. RESULTS: A standard workflow is presented exemplifying how ERGtools2 can be used to efficiently import, pre-process and analyse ERG data. Following this workflow, basic ERG measurements and visualisation of a single exam as well as group statistics are obtained. Moreover, special use cases are described, including for the handling of noisy data and the storage of data in the HDF5 format to ensure long-term preservation and accessibility. CONCLUSIONS: ERGtools2 provides a comprehensive, flexible, and device-independent solution for visual electrophysiology data analysis. Its emphasis on maintaining raw data integrity, combined with advanced processing and analysis capabilities, makes it a useful tool for preclinical and clinical research applications. The open-source nature and the use of open data formats promote reproducibility and data sharing in visual neurosciences.
Disentangling the Component Processes in Complex Planning Impairments Following Ventromedial Prefrontal Lesions
Damage to the ventromedial prefrontal cortex (vmPFC) in humans disrupts planning abilities in naturalistic settings. However, it is unknown which components of planning are affected in these patients, including selecting the relevant information, simulating future states, or evaluating between these states. To address this question, we leveraged computational paradigms to investigate the role of vmPFC in planning, using the board game task “Four-in-a-Row” (18 lesion patients, 9 female; 30 healthy control participants, 16 female) and the simpler “Two-Step” task measuring model-based reasoning (49 lesion patients, 27 female; 20 healthy control participants, 13 female). Damage to vmPFC disrupted performance in Four-in-a-Row compared with both control lesion patients and healthy age-matched controls. We leveraged a computational framework to assess different component processes of planning in Four-in-a-Row and found that impairments following vmPFC damage included shallower planning depth and a tendency to overlook game-relevant features. In the “Two-Step” task, which involves binary choices across a short future horizon, we found little evidence of planning in all groups and no behavioral differences between groups. Complex yet computationally tractable tasks such as “Four-in-a-Row” offer novel opportunities for characterizing neuropsychological planning impairments, which in vmPFC patients we find are associated with oversights and reduced planning depth.
Human motor cortical gamma activity relates to GABAergic intracortical inhibition and motor learning
Abstract Gamma activity (γ, >30 Hz) is universally demonstrated across brain regions and species. However, the physiological basis and functional role of γ sub-bands (slow-γ, mid-γ, fast-γ) have been predominantly studied in rodent hippocampus; γ activity in the human neocortex is much less well understood. We use electrophysiology, non-invasive brain stimulation and several motor tasks to examine the properties of sensorimotor γ activity sub-bands and their relationship to both local GABAergic activity and motor learning. Data from three experimental studies are presented. Experiment 1 (N = 33) comprises magnetoencephalography (MEG), transcranial magnetic stimulation (TMS), and a motor learning paradigm; experiment 2 (N = 19) uses MEG and motor learning; and experiment 3 (N = 18) uses EEG and TMS. We characterised two distinct γ sub-bands (slow-γ, mid-γ) which show a movement-related increase in activity during unilateral index finger movements and are characterised by distinct temporal-spectral-spatial profiles. Bayesian correlation analysis revealed strong evidence for a positive relationship between slow-γ (~30-60Hz) peak frequency and GABAergic intracortical inhibition (as assessed using the TMS-metric short interval intracortical inhibition). There was also moderate evidence for a relationship between the power of the movement-related mid-γ activity (60-90Hz) and motor learning. These relationships were neurochemical- and frequency-specific. These data provide new insights into the neurophysiological basis and functional roles of γ activity in human M1 and allow the development of a new theoretical framework for γ activity in the human neocortex.
Neuropathological Evidence of Reduced Amyloid Beta and Neurofibrillary Tangles in Multiple Sclerosis Cortex
Multiple sclerosis (MS) and Alzheimer's disease are neurodegenerative diseases with age‐related disability accumulation. In MS, inflammation spans decades, whereas AD is characterized by Aβ plaques and neurofibrillary tangles (NFT). Few studies explore accumulation of amyloids in MS. We examined Aβ deposition and NFT density in temporal and frontal cortices from postmortem MS (n = 75) and control (n = 66) cases. Compared with controls, MS cases showed reduced Aβ, especially in those aged <65 years, and reduced NFT, notably in cases aged >65 years. Aβ deposition predicted greater NFT density both in MS cases and controls. MS‐related factors may affect Aβ/NFT deposition and/or clearance, offering new therapeutic insights for both diseases. ANN NEUROL 2025
Process evaluation in a randomised controlled trial of DREAMS-START (dementia related manual for sleep; strategies for relatives) for sleep disturbance in people with dementia and their carers.
INTRODUCTION: DREAMS-START is a multicomponent intervention targeting sleep disturbance in people with dementia. To enhance understanding of the DREAMS-START randomised controlled trial, which showed improved sleep in the intervention compared to the control arm, we conducted a process evaluation exploring (i) DREAMS-START delivery, (ii) behaviour change mechanisms and (iii) contextual factors impacting outcomes. METHODS: Mixed-methods design. We measured intervention adherence, fidelity and additional therapeutic process measures. We interviewed a sub-sample of intervention arm family carers and facilitators delivering DREAMS-START. We analysed data thematically guided by a prespecified theory of change logic model informed by the Theoretical Domains Framework. We measured movement using an actigraph worn by the person with dementia at baseline and at four- and eight-month follow-ups to explore potential mechanisms of action. RESULTS: Attendance was good (82.8% attended ≥4/6 sessions). Mean fidelity score (95.4%; SD 0.08) and median score for all four process measures assessed (5/5; IQR 5-5) were high. We interviewed 43/188 family carers and 9/49 DREAMS-START facilitators. We identified three overarching themes aligned with our model: (i) knowledge and facilitation enable behaviour change, (ii) increasing sleep pressure and developing skills to manage sleep disturbances and (iii) Establishing a routine and sense of control. We were unable to collect sufficient data for pre-specified actigraphy analyses. CONCLUSION: Despite competing demands, carers attended DREAMS-START. It promoted behaviour change through supportive in-session reflection, increasing carer knowledge and skills. This was embedded between sessions and actions were positively reinforced as carers experienced changes. Results will inform future implementation in clinical services.