Myelin bilayer mapping in the human brain in vivo

PURPOSE To quantitatively map the myelin lipid-protein bilayer in the live human brain. METHODS This goal was pursued by integrating a multi-TE acquisition approach targeting ultrashort T$_{2}$ signals with voxel-wise fitting to a three-component signal model. Imaging was performed at 3 T in two healthy volunteers using high-performance RF and gradient hardware and the HYFI sequence. The design of a suitable imaging protocol faced substantial constraints concerning SNR, imaging volume, scan time, and RF power deposition. Model fitting to data acquired using the proposed protocol was made feasible through simulation-based optimization, and filtering was used to condition noise presentation and overall depiction fidelity. RESULTS A multi-TE protocol (11 TEs of 20-780 μs) for in vivo brain imaging was developed in adherence with applicable safety regulations and practical scan time limits. Data acquired using this protocol produced accurate model fitting results, validating the suitability of the protocol for this purpose. Structured, grainy texture of myelin bilayer maps was observed and determined to be a manifestation of correlated image noise resulting from the employed acquisition strategy. Map quality was significantly improved by filtering to uniformize the k-space noise distribution and simultaneously extending the k-space support. The final myelin bilayer maps provided selective depiction of myelin, reconciling competitive resolution (1.4 mm) with adequate SNR and benign noise texture. CONCLUSION Using the proposed technique, quantitative maps of the myelin bilayer can be obtained in vivo. These maps offer unique information content with potential applications in basic research, diagnosis, disease monitoring, and drug development

Structural magnetic resonance imaging findings and histopathological correlations in motor neuron diseases—A systematic review and meta-analysis

OBJECTIVES The lack of systematic evidence on neuroimaging findings in motor neuron diseases (MND) hampers the diagnostic utility of magnetic resonance imaging (MRI). Thus, we aimed at performing a systematic review and meta-analysis of MRI features in MND including their histopathological correlation. METHODS In a comprehensive literature search, out of 5941 unique publications, 223 records assessing brain and spinal cord MRI findings in MND were eligible for a qualitative synthesis. 21 records were included in a random effect model meta-analysis. RESULTS Our meta-analysis shows that both T2-hyperintensities along the corticospinal tracts (CST) and motor cortex T2$^{*}$-hypointensitites, also called "motor band sign", are more prevalent in ALS patients compared to controls [OR 2.21 (95%-CI: 1.40-3.49) and 10.85 (95%-CI: 3.74-31.44), respectively]. These two imaging findings correlate to focal axonal degeneration/myelin pallor or glial iron deposition on histopathology, respectively. Additionally, certain clinical MND phenotypes such as amyotrophic lateral sclerosis (ALS) seem to present with distinct CNS atrophy patterns. CONCLUSIONS Although CST T2-hyperintensities and the "motor band sign" are non-specific imaging features, they can be leveraged for diagnostic workup of suspected MND cases, together with certain brain atrophy patterns. Collectively, this study provides high-grade evidence for the usefulness of MRI in the diagnostic workup of suspected MND cases. SYSTEMATIC REVIEW REGISTRATION https://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42020182682

Large Language Models (LLM) - based methods for text processing and analysis in the biomedical literature – a scoping review

We aim at mapping the field of large language models in the context of processing and analysing biomedical text. Concretely, Which tasks in the domain of Biomedical Natural Language Processing (BioNLP) are being tackled with LLMs, e.g. Named Entity Recognition, Information Extraction, Text Classification? Which LLMs architectures are used for those BioNLP tasks, e.g. BERT, combination of Transformer models and other ML algorithms like BM25

PsyNamic: A living systematic review of psychedelic therapy in psychiatric disorders

The resurgence of interest in the therapeutic potential of psychedelic substances for psychiatric disorders has heralded a new era of clinical research. Substances such as LSD, psilocybin, mescaline, DMT, 5-MeO-DMT, MDMA, ketamine, ibogaine, and salvinorin A are being investigated for their efficacy in treating conditions like eating disorders, depression, and anxiety. However, the rapid accumulation of clinical trial data presents a challenge for manual synthesis and the continuous updating of evidence. This study aims to address this gap by establishing a living systematic review that dynamically incorporates new research findings on the use of psychedelic substances in psychiatric treatment. Utilizing natural language processing (NLP) techniques, including large language models, we plan to automate the classification of studies and extraction of relevant data. Our approach will enable the real-time synthesis of evidence, ensuring that the most current data is readily accessible. The outcomes of this research will be freely available in an online data warehouse, providing a comprehensive and up-to-date resource for both clinicians planning future trials and interested laypersons seeking evidence-based information on psychedelic therapy. This endeavor promises to enhance the efficiency of evidence synthesis in the burgeoning field of psychedelic research and offer insights for the evidence-based application of psychedelic therapy in psychiatric care for lay people

Mapping the myelin bilayer with short-T2_{2} MRI: Methods validation and reference data for healthy human brain

PURPOSE To explore the properties of short-T$_{2}$ signals in human brain, investigate the impact of various experimental procedures on these properties and evaluate the performance of three-component analysis. METHODS Eight samples of non-pathological human brain tissue were subjected to different combinations of experimental procedures including D$_{2}$ O exchange and frozen storage. Short-T$_{2}$ imaging techniques were employed to acquire multi-TE (33-2067 μs) data, to which a three-component complex model was fitted in two steps to recover the properties of the underlying signal components and produce amplitude maps of each component. For validation of the component amplitude maps, the samples underwent immunohistochemical myelin staining. RESULTS The signal component representing the myelin bilayer exhibited super-exponential decay with T$_{2,min}$ of 5.48 μs and a chemical shift of 1.07 ppm, and its amplitude could be successfully mapped in both white and gray matter in all samples. These myelin maps corresponded well to myelin-stained tissue sections. Gray matter signals exhibited somewhat different components than white matter signals, but both tissue types were well represented by the signal model. Frozen tissue storage did not alter the signal components but influenced component amplitudes. D$_{2}$ O exchange was necessary to characterize the non-aqueous signal components, but component amplitude mapping could be reliably performed also in the presence of H$_{2}$ O signals. CONCLUSIONS The myelin mapping approach explored here produced reasonable and stable results for all samples. The extensive tissue and methodological investigations performed in this work form a basis for signal interpretation in future studies both ex vivo and in vivo

How successful is bench-to-bedside translation in animal research – a systematic review

Bench-to-bedside translation, e.g. eventual market approval of a therapy tested in animals, is considered to be very low in animal research (Bespalov et al., 2016). However, although bench-to-bedside translation has been assessed in certain biomedicine fields, no comprehensive analysis has investigated the extent of successful translation within different biomedicine subfields. In addition, these rates have not been systematically compared with translational rates in animal free research fields. Thus, we aim at systematically evaluating bench-to-bedside translation in biomedicine based on animal meta studies and compare the extent of bench-to-bedside translation to preclinical research fields without the use of animal experiments. Objective: Summarize the current evidence on bench-to-bedside translation from systematic reviews and/or meta-analyses of animal studies. How is bench-to-bedside translation defined? How successful is bench-to-bedside translation in animal research – on a qualitative or quantitative level and in different biomedicine branches (e.g. cancer or neuroscience)? The study will focus on bench-to-bedside translation of interventions with the goal of improving outcomes in animal models of human diseases. Compare bench-to-bedside translation with translational rates in animal free research fields (e.g. Medical Device Approval)

Credibility of the data and code availability statement

Data availability statements have been introduced as a measure to facilitate access to data to foster Open Science practices. Recent studies to probe the availability of such primary data showed that only a minority of study authors is willing to share their primary data. However, in addition to the primary data, also the code to analyze the data and associated meta-data is critical when aiming at reproducing or replicating published research findings. The goal of our study is to further scrutinize the data and code availability statement. More concretely, our study aims at answering the following primary research question: Are authors willing to share primary data, all associated code and material necessary to reproduce the research finding as well as any meta-data from their primary study? In addition, we aim at answering the following secondary research questions: 1) Is there a qualitative difference in data/code availability between less or more acknowledged journals?, And 2) Is data/code from more recent studies more easily available and accessible compared to older studies? We will focus on three neuroscience research branches: multiple sclerosis, Alzheimer’s Disease, and stroke; as well as two publishers/journals which mandate a data availability statement (Frontiers in and Nature Neuroscience). Since data from human patients is considered sensitive, we will solely consider preclinical studies. We will systematically identify eligible publications by PRISMA-conform systematic review methodology

Neuroimaging findings in preclinical amyotrophic lateral sclerosis models-How well do they mimic the clinical phenotype? A systematic review

BACKGROUND AND OBJECTIVES Animal models for motor neuron diseases (MND) such as amyotrophic lateral sclerosis (ALS) are commonly used in preclinical research. However, it is insufficiently understood how much findings from these model systems can be translated to humans. Thus, we aimed at systematically assessing the translational value of MND animal models to probe their external validity with regards to magnetic resonance imaging (MRI) features. METHODS In a comprehensive literature search in PubMed and Embase, we retrieved 201 unique publications of which 34 were deemed eligible for qualitative synthesis including risk of bias assessment. RESULTS ALS animal models can indeed present with human ALS neuroimaging features: Similar to the human paradigm, (regional) brain and spinal cord atrophy as well as signal changes in motor systems are commonly observed in ALS animal models. Blood-brain barrier breakdown seems to be more specific to ALS models, at least in the imaging domain. It is noteworthy that the G93A-SOD1 model, mimicking a rare clinical genotype, was the most frequently used ALS proxy. CONCLUSIONS Our systematic review provides high-grade evidence that preclinical ALS models indeed show imaging features highly reminiscent of human ALS assigning them a high external validity in this domain. This opposes the high attrition of drugs during bench-to-bedside translation and thus raises concerns that phenotypic reproducibility does not necessarily render an animal model appropriate for drug development. These findings emphasize a careful application of these model systems for ALS therapy development thereby benefiting refinement of animal experiments. SYSTEMATIC REVIEW REGISTRATION https://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42022373146