The importance of nerve microenvironment for schwannoma development

Schwannomas are predominantly benign nerve sheath neoplasms caused by Nf2 gene inactivation. Presently, treatment options are mainly limited to surgical tumor resection due to the lack of effective pharmacological drugs. Although the mechanistic understanding of Nf2 gene function has advanced, it has so far been primarily restricted to Schwann cell-intrinsic events. Extracellular cues determining Schwann cell behavior with regard to schwannoma development remain unknown. Here we show pro-tumourigenic microenvironmental effects on Schwann cells where an altered axonal microenvironment in cooperation with injury signals contribute to a persistent regenerative Schwann cell response promoting schwannoma development. Specifically in genetically engineered mice following crush injuries on sciatic nerves, we found macroscopic nerve swellings in mice with homozygous nf2 gene deletion in Schwann cells and in animals with heterozygous nf2 knockout in both Schwann cells and axons. However, patient-mimicking schwannomas could only be provoked in animals with combined heterozygous nf2 knockout in Schwann cells and axons. We identified a severe re-myelination defect and sustained macrophage presence in the tumor tissue as major abnormalities. Strikingly, treatment of tumor-developing mice after nerve crush injury with medium-dose aspirin significantly decreased schwannoma progression in this disease model. Our results suggest a multifactorial concept for schwannoma formation-emphasizing axonal factors and mechanical nerve irritation as predilection site for schwannoma development. Furthermore, we provide evidence supporting the potential efficacy of anti-inflammatory drugs in the treatment of schwannomas

A methodology to involve domain experts and machine learning techniques in the design of human-centered algorithms

Part 2: MethodologicalInternational audienceMachine learning techniques are increasingly applied in Decision Support Systems. The selection processes underlying a conclusion often become black-boxed. Thus, the decision flow is not always comprehensible by developers or end users. It is unclear what the priorities are and whether all of the relevant information is used. In order to achieve human interpretability of the created algorithms, it is recommended to include domain experts in the modelling phase. Their knowledge is elicited through a combination of machine learning and social science techniques. The idea is not new, but it remains a challenge to extract and apply the experts’ experience without overburdening them. The current paper describes a methodology set to unravel, define and categorize the implicit and explicit domain knowledge in a less intense way by making use of co-creation to design human-centered algorithms, when little data is available. The methodology is applied to a case in the health domain, targeting a rheumatology triage problem. The domain knowledge is obtained through dialogue, by alternating workshops and data science exercises

Potential surrogate markers of cerebral microvascular angiopathy in asymptomatic subjects at risk of stroke

Cerebral microvascular angiopathy (MVA) is associated with clinical vascular risk factors and is characterised by histological changes, including thickening of the walls of arterial vessels and dilatation of the Virchow-Robin spaces (VRS). We have previously described two novel biomarkers of MVA based on magnetic resonance imaging (MRI), VRS dilatation and abnormalities in the transfer of systolic arterial pulsation to the ventricular CSF, which occur as a result of decreased cerebral arterial compliance. These are associated with vascular dementia and treatment-resistant late onset depression. We studied a group of normal subjects at risk of cerebrovascular disease to determine if these biomarkers are present in patients who have no evidence of symptomatic vascular disease. We studied 31 subjects, 16 with three or more vascular risk factors and 15 with one or less significant risk factors. We measured arterial blood flow and CSF flow in the cerebral aqueduct, white matter lesion load, and the distribution and number of VRS. There were significant differences in CSF pulsatility and in VRS in the basal ganglia between the two groups, but no differences in white matter lesion load. We conclude that asymptomatic subjects at risk of stroke have MRI evidence of MVA before white matter lesions become apparent