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Biophysical effects and neuromodulatory dose of transcranial ultrasonic stimulation.
Transcranial ultrasonic stimulation (TUS) has the potential to usher in a new era for human neuroscience by allowing spatially precise and high-resolution non-invasive targeting of both deep and superficial brain regions. Currently, fundamental research on the mechanisms of interaction between ultrasound and neural tissues is progressing in parallel with application-focused research. However, a major hurdle in the wider use of TUS is the selection of optimal parameters to enable safe and effective neuromodulation in humans. In this paper, we will discuss the major factors that determine the efficacy of TUS. We will discuss the thermal and mechanical biophysical effects of ultrasound, which underlie its biological effects, in the context of their relationships with tunable parameters. Based on this knowledge of biophysical effects, and drawing on concepts from radiotherapy, we propose a framework for conceptualising TUS dose.
Dataset for Brain 2025 paper: nerve pathology in whiplash
This the dataset for the Fundaun et al paper in Brain 2025. it contains de-identified data of the included figures.
Considerations and recommendations from the ISMRM diffusion study group for preclinical diffusion MRI: Part 2—Ex vivo imaging: Added value and acquisition
AbstractThe value of preclinical diffusion MRI (dMRI) is substantial. While dMRI enables in vivo non‐invasive characterization of tissue, ex vivo dMRI is increasingly being used to probe tissue microstructure and brain connectivity. Ex vivo dMRI has several experimental advantages including higher SNR and spatial resolution compared to in vivo studies, and enabling more advanced diffusion contrasts for improved microstructure and connectivity characterization. Another major advantage of ex vivo dMRI is the direct comparison with histological data, as a crucial methodological validation. However, there are a number of considerations that must be made when performing ex vivo experiments. The steps from tissue preparation, image acquisition and processing, and interpretation of results are complex, with many decisions that not only differ dramatically from in vivo imaging of small animals, but ultimately affect what questions can be answered using the data. This work represents “Part 2” of a three‐part series of recommendations and considerations for preclinical dMRI. We describe best practices for dMRI of ex vivo tissue, with a focus on the value that ex vivo imaging adds to the field of dMRI and considerations in ex vivo image acquisition. We first give general considerations and foundational knowledge that must be considered when designing experiments. We briefly describe differences in specimens and models and discuss why some may be more or less appropriate for different studies. We then give guidelines for ex vivo protocols, including tissue fixation, sample preparation, and MR scanning. In each section, we attempt to provide guidelines and recommendations, but also highlight areas for which no guidelines exist (and why), and where future work should lie. An overarching goal herein is to enhance the rigor and reproducibility of ex vivo dMRI acquisitions and analyses, and thereby advance biomedical knowledge.
Considerations and recommendations from the ISMRM Diffusion Study Group for preclinical diffusion MRI: Part 3—Ex vivo imaging: Data processing, comparisons with microscopy, and tractography
AbstractPreclinical diffusion MRI (dMRI) has proven value in methods development and validation, characterizing the biological basis of diffusion phenomena, and comparative anatomy. While dMRI enables in vivo non‐invasive characterization of tissue, ex vivo dMRI is increasingly being used to probe tissue microstructure and brain connectivity. Ex vivo dMRI has several experimental advantages that facilitate high spatial resolution and high SNR images, cutting‐edge diffusion contrasts, and direct comparison with histological data as a methodological validation. However, there are a number of considerations that must be made when performing ex vivo experiments. The steps from tissue preparation, image acquisition and processing, and interpretation of results are complex, with many decisions that not only differ dramatically from in vivo imaging of small animals, but ultimately affect what questions can be answered using the data. This work concludes a three‐part series of recommendations and considerations for preclinical dMRI. Herein, we describe best practices for dMRI of ex vivo tissue, with a focus on image pre‐processing, data processing, and comparisons with microscopy. In each section, we attempt to provide guidelines and recommendations but also highlight areas for which no guidelines exist (and why), and where future work should lie. We end by providing guidelines on code sharing and data sharing and point toward open‐source software and databases specific to small animal and ex vivo imaging.
Prominent astrocytic alpha-synuclein pathology with unique post-translational modification signatures unveiled across Lewy body disorders.
Alpha-synuclein (aSyn) is a pre-synaptic monomeric protein that can form aggregates in neurons in Parkinson's disease (PD), Parkinson's disease with dementia (PDD) and dementia with Lewy bodies (DLB), and in oligodendrocytes in multiple system atrophy (MSA). Although aSyn in astrocytes has previously been described in PD, PDD and DLB, the biochemical properties and topographical distribution of astrocytic aSyn have not been studied in detail. Here, we present a systematic investigation of aSyn astrocytic pathology using an expanded antibody toolset covering the entire sequence and key post-translational modifications (PTMs) of aSyn in Lewy body disorders (LBDs) and in MSA. Astrocytic aSyn was detected in the limbic cortical regions of LBDs but were absent in main pathological regions of MSA. The astrocytic aSyn was revealed only with antibodies against the mid N-terminal and non-amyloid component (NAC) regions covering aSyn residues 34-99. The astroglial accumulations were negative to canonical aSyn aggregation markers, including p62, ubiquitin and aSyn pS129, but positive for phosphorylated and nitrated forms of aSyn at Tyrosine 39 (Y39), and not resistant to proteinase K. Our findings suggest that astrocytic aSyn accumulations represent a major part of aSyn pathology in LBDs and possess a distinct sequence and PTM signature that is characterized by both N- and C-terminal truncations and modifications at Y39. This is the first description that aSyn accumulations are made solely from N- and C-terminally cleaved aSyn species and the first report demonstrating that astrocytic aSyn is a mixture of Y39 phosphorylated and nitrated species. These observations underscore the importance of systematic characterization of aSyn accumulations in different cell types to capture the aSyn pathological diversity in the brain. Our findings combined with further studies on the role of astrocytic pathology in the progression of LBDs can pave the way towards identifying novel disease mechanisms and therapeutic targets.
Acute urinary retention in a 27-year-old male secondary to benign prostatic hyperplasia treated with Holmium Enucleation of the Prostate (HOLEP)
Introduction: Benign prostatic hyperplasia (BPH) is common in the ageing male. Clinical manifestations like retention impact on a patient’s quality of life. Alterations in androgen activity at the androgen receptor complex level in the prostate contribute to prostatic hyperplasia with the highest incidence occurring in males in their 70’s. There remains a paucity of cases in young males who develop acute urinary retention secondary to BPH. We present a case of a 27-year-old male who developed acute urinary retention secondary to BPH who required a Holmium Laser Enucleation of his Prostate (HOLEP). Case description: A 27 year old man was admitted in acute urinary retention. BPH was diagnosed via way of radiological imaging and histological assessment. After pre-operative sperm banking and suprapubic catheterisation, the patient underwent a HOLEP. He had biochemically confirmed hypogonadotrophic hypogonadism which was at odds with his muscular, physical appearance. Total testosterone levels had fluctuated following admission suggesting an exogenous substance was interfering with the hypothalamic-pituitary-gonadal axis but he denied exogenous steroid use. Result: The patient successfully passed his voiding trial on the second post-operative day and remained catheter free. Post-operative uroflowmetry and sexual function remain unknown as patient disengaged with follow up. Conclusion: HOLEP prostatectomy is a safe and effective way of managing BPH in younger patients following sperm banking and assessment by endocrinology.
Neuropathological Assessment as an Endpoint in Clinical Trial Design.
Different neurodegenerative conditions can have complex, overlapping clinical presentations that make accurate diagnosis during life very challenging. For this reason, confirmation of the clinical diagnosis still requires postmortem verification. This is particularly relevant for clinical trials of novel therapeutics where it is important to ascertain what disease- and/or pathology-modifying effects the therapeutics have had. Furthermore, it is important to confirm that patients in the trial had the correct clinical diagnosis as this will have a major bearing on the interpretation of trial results. Here we present a simple protocol for pathological assessment of neurodegenerative changes.
Validation of Korean Version of the Oxford Cognitive Screen (K-OCS), a Post Stroke-Specific Cognitive Screening Tool
Objective: To establish and evaluate the validity of the recently developed Korean version of the Oxford Cognitive Screen (K-OCS), this study verified its reliability, validity, and diagnostic accuracy.Methods: Between November 2021 and December 2023, we recruited 72 patients with stroke from our hospital who agreed to participate in the study. The patients were repeatedly tested using K-OCS by the same or different assessors to estimate inter- and intra-rater reliability. To demonstrate the validity and usability of K-OCS, the test results of screening tools currently used in clinical practice, including the Korean-Mini Mental State Examination and the Korean version of the Montreal Cognitive Assessment, were used in comparison analyses.Results: The subtests of K-OCS demonstrated excellent inter-rater reliability (intra-class correlation coefficient [ICC]=0.914–0.998) and test–retest reliability (ICC=0.913–0.994). We found moderate-to-strong correlations for convergent validity for the subsets (r=0.378– 0.979, p<0.01), and low-to-moderate discriminant validity correlations. The optimal cut-offs estimated for the subtests of the K-OCS showed a good-to-high range of specificity (94.8%– 100%). The positive predictive value was 58.2%–100% and negative predictive value was 65.6%–98.4%. Sensitivity was estimated at 25.6%–86.9%.Conclusion: The results of this study indicate that K-OCS is a reliable and valid tool for screening cognitive impairment in patients post-stroke.
Prediction models for treatment response in migraine: a systematic review and meta-analysis.
BackgroundMigraine is a complex neurological disorder with significant clinical variability, posing challenges for effective management. Multiple treatments are available for migraine, but individual responses vary widely, making accurate prediction crucial for personalized care. This study aims to examine the use of statistical and machine learning models to predict treatment response in migraine patients.MethodsA systematic review and meta-analysis were conducted to assess the performance and quality of predictive models for migraine treatment response. Relevant studies were identified from databases such as PubMed, Cochrane Register of Controlled Trials, Embase, and Web of Science, up to 30th of November 2024. The risk of bias was evaluated using the PROBAST tool, and adherence to reporting standards was assessed with the TRIPOD + AI checklist.ResultsAfter screening 1,927 documents, ten studies met the inclusion criteria, and six were included in a quantitative synthesis. Key data extracted included sample characteristics, intervention types, response outcomes, modeling methods, and predictive performance metrics. A pooled analysis of the area under the curve (AUC) yielded a value of 0.86 (95% CI: 0.67-0.95), indicating good predictive performance. However, the included studies generally had a high risk of bias, particularly in the analysis domain, as assessed by the PROBAST tool.ConclusionThis review highlights the potential of statistical and machine learning models in predicting treatment response in migraine patients. However, the high risk of bias and significant heterogeneity emphasize the need for caution in interpretation. Future research should focus on developing models using high-quality, comprehensive, and multicenter datasets, rigorous external validation, and adherence to standardized guidelines like TRIPOD + AI. Incorporating multimodal magnetic resonance imaging (MRI) data, exploring migraine symptom-treatment interactions, and establishing uniform methodologies for outcome measures, sample size calculations, and missing data handling will enhance model reliability and clinical applicability, ultimately improving patient outcomes and reducing healthcare burdens.Trial registrationPROSPERO, CRD42024621366.
How and why eLife selects papers for peer review
When deciding which submissions should be peer reviewed, eLife editors consider whether they will be able to find high-quality reviewers, and whether the reviews will be valuable to the scientific community.