Biology subjects

Ineichen, B. V.

Publications and source records attributed to Ineichen, B. V..

4 recordsLinked to original sources

bioRxiv2023

Auto-STEED: A data mining tool for automated extraction of experimental parameters and risk of bias items from in vivo publications

BackgroundSystematic reviews, i.e., research summaries that address focused questions in a structured and reproducible manner, are a cornerstone of evidence-based medicine and research. However, certain systematic review steps such as data extraction are labour-intensive which hampers their applicability, not least with the rapidly expanding body of biomedical literature. ObjectiveTo bridge this gap, we aimed at developing a data mining tool in the R programming environment to automate data extraction from neuroscience in vivo publications. The function was trained on a literature corpus (n=45 publications) of animal motor neuron disease studies and tested in two validation corpora (motor neuron diseases, n=31 publications; multiple sclerosis, n=244 publications). ResultsOur data mining tool Auto-STEED (Automated and STructured Extraction of Experimental Data) was able to extract key experimental parameters such as animal models and species as well as risk of bias items such as randomization or blinding from in vivo studies. Sensitivity and specificity were over 85 and 80%, respectively, for most items in both validation corpora. Accuracy and F-scores were above 90% and 0.9 for most items in the validation corpora. Time savings were above 99%. ConclusionsOur developed text mining tool Auto-STEED is able to extract key experimental parameters and risk of bias items from the neuroscience in vivo literature. With this, the tool can be deployed to probe a field in a research improvement context or to replace one human reader during data extraction resulting in substantial time-savings and contribute towards automation of systematic reviews. The function is available on Github.

neuroscience↗

bioRxiv2023

Dilated Virchow-Robin Spaces are a Marker for Arterial Disease in Multiple Sclerosis

Virchow-Robin spaces (VRS) have been associated with neurodegeneration and neuroinflammation. However, it remains uncertain to what degree non-dilated or dilated VRS reflect specific features of neuroinflammatory pathology. Thus, we aimed at investigating the clinical relevance of VRS as imaging biomarker in multiple sclerosis (MS) and to correlate VRS to their histopathologic signature. In a cohort study comprising 205 MS patients (including a validation cohort) and 30 control subjects, we assessed the association of non-dilated and dilated VRS to clinical and magnetic resonance imaging (MRI) out-comes. Brain blocks from 6 MS patients and 3 non-MS controls were histopathologically processed to correlate VRS to their tissue substrate. The count of dilated centrum semiovale VRS was associated with increased T1 and T2 lesion volumes. There was no systematic spatial colocalization of dilated VRS with MS lesions. At tissue level, VRS mostly corresponded to arteries and were not associated with MS pathological hallmarks. Interestingly, dilated VRS in MS were associated with signs of small vessel disease. Contrary to prior beliefs, these observations suggest that VRS in MS do not associate with accumulation of immune cells. But instead, these findings indicate vascular pathology as a driver and/or consequence of neuroinflammatory pathology for this imaging feature.

neuroscience↗

bioRxiv2021

Leptomeningeal Enhancement in Multiple Sclerosis and Other Neurological Diseases: A Systematic Review and Meta-Analysis

BackgroundThe lack of systematic evidence on leptomeningeal enhancement (LME) on MRI in neurological diseases, including multiple sclerosis (MS), hampers its interpretation in clinical routine and research settings. PurposeTo perform a systematic review and meta-analysis of MRI LME in MS and other neurological diseases. Materials and MethodsIn a comprehensive literature search in Medline, Scopus, and Embase, out of 2292 publications, 459 records assessing LME in neurological diseases were eligible for qualitative synthesis. Of these, 135 were included in a random-effects model meta-analysis with subgroup analyses for MS. ResultsOf eligible publications, 161 investigated LME in neoplastic neurological (n=2392), 91 in neuroinfectious (n=1890), and 75 in primary neuroinflammatory diseases (n=4038). The LME-proportions for these disease classes were 0.47 [95%-CI: 0.37-0.57], 0.59 [95%-CI: 0.47-0.69], and 0.26 [95%-CI: 0.20-0.35], respectively. In a subgroup analysis comprising 1605 MS cases, LME proportion was 0.30 [95%-CI 0.21-0.42] with lower proportions in relapsing-remitting (0.19 [95%-CI 0.13-0.27]) compared to progressive MS (0.39 [95%-CI 0.30-0.49], p=0.002) and higher proportions in studies imaging at 7T (0.79 [95%-CI 0.64-0.89]) compared to lower field strengths (0.21 [95%-CI 0.15-0.29], p<0.001). LME in MS was associated with longer disease duration (mean difference 2.2 years [95%-CI 0.2-4.2], p=0.03), higher Expanded Disability Status Scale (mean difference 0.6 points [95%-CI 0.2-1.0], p=0.006), higher T1 (mean difference 1.6ml [95%-CI 0.1-3.0], p=0.04) and T2 lesion load (mean difference 5.9ml [95%-CI 3.2-8.6], p<0.001), and lower cortical volume (mean difference -21.3ml [95%-CI -34.7--7.9], p=0.002). ConclusionsOur study provides high-grade evidence for the substantial presence of LME in MS and a comprehensive panel of other neurological diseases. Our data could facilitate differential diagnosis of LME in clinical settings. Additionally, our meta-analysis corroborates that LME is associated with key clinical and imaging features of MS. PROSPERO No: CRD42021235026. Summary statementOur systematic review and meta-analysis synthesize leptomeningeal enhancement proportions across a comprehensive panel of neurological diseases, including multiple sclerosis, and assesses its prognostic value in multiple sclerosis. Summary dataO_LILeptomeningeal enhancement (LME) is a nonspecific imaging feature present across many neurological disorders, including neoplasm, infection, and primary neuroinflammation. C_LIO_LIThe presence of LME is associated with worse clinical and imaging outcomes in multiple sclerosis, justifying its ascertainment in clinical practice. C_LIO_LINeuroinflammatory animal models can be used to further investigate the pathophysiology of LME, including its pathological tissue signature and/or its association with cortical pathology. C_LI

neuroscience↗

bioRxiv2021

In Vivo MRI of Endogenous Remyelination in a Nonhuman Primate Model of Multiple Sclerosis

Remyelination is crucial for recovery from inflammatory demyelination in multiple sclerosis (MS). Investigating remyelination in vivo using magnetic resonance imaging (MRI) is difficult in MS, where collecting serial short-interval scans is challenging. Using experimental autoimmune encephalomyelitis (EAE) in common marmosets, a model of MS that recapitulates focal cerebral MS lesions, we investigated whether remyelination can be detected and characterized noninvasively. In 6 animals followed with multisequence 7-tesla MRI, 36 focal lesions, classified as demyelinated or remyelinated based on signal intensity on proton density-weighted images, were subsequently assessed with histopathology. Remyelination occurred in 5 of 6 marmosets and 51% of lesions. Radiological-pathological comparison showed high sensitivity (88%) and specificity (90%) for detecting remyelination by in vivo MRI. This study demonstrates the prevalence of spontaneous remyelination in marmoset EAE and the ability of in vivo MRI to detect it, with implications for preclinical testing of pro-remyelinating agents and translation to clinical practice.

neuroscience↗