Novel COL4A1 mutations cause cerebral small vessel disease by haploinsufficiency

Mutations in COL4A1 have been identified in families with hereditary small vessel disease of the brain presumably due to a dominant-negative mechanism. Here, we report on two novel mutations in COL4A1 in two families with porencephaly, intracerebral hemorrhage and severe white matter disease caused by haploinsufficiency. Two families with various clinical presentations of cerebral microangiopathy and autosomal dominant inheritance were examined. Clinical, neuroradiological and genetic investigations were performed. Electron microscopy of the skin was also performed. In one of the families, sequence analysis revealed a one base deletion, c.2085del, leading to a frameshift and a premature stopcodon, p.(Gly696fs). In the other family, a splice site mutation was identified, c.2194-1G>A, which most likely leads to skipping of an exon with a frameshift and premature termination as a result. In fibroblasts of affected individuals from both the families, nonsense-mediated decay (NMD) of the mutant COL4A1 messenger RNAs (mRNAs) and a clear reduction of COL4A1 protein expression were demonstrated, indicating haploinsufficiency of COL4A1. Moreover, thickening of the capillary basement membrane in the skin was documented, similar to reports in patients with COL4A1 missense mutations. These findings suggest haploinsufficiency, a different mechanism from the commonly assumed dominant-negative effect, for COL4A1 mutations as a cause of (antenatal) intracerebral hemorrhage and white matter disease. © The Author 2012. Published by Oxford University Press. All rights reserved

Acute Stroke Imaging Research Roadmap II.

The Stroke Imaging Research (STIR) Group, the American Society of Neuroradiology, and the Foundation of the American Society of Neuroradiology sponsored a series of working group meetings >12 months, with the final meeting occurring during the Stroke Treatment Academy Industry Roundtable (STAIR) on March 9 to 10, 2013, in Washington, DC. This process brought together vascular neurologists, neuroradiologists, neuroimaging research scientists, members of the National Institute of Neurological Disorders and Stroke, industry representatives, and members of the US Food and Drug Administration to discuss stroke imaging research priorities, especially in the light of the recent negative results of acute stroke clinical trials that tested the concept of penumbral imaging selection. The goal of this process was to propose a research roadmap for the next 5 years. STIR recommendations include (1) the use of standard terminology, aligned with the National Institute of Neurological Disorders and Stroke Common Data Elements. ; (2) a standardized imaging assessment of revascularization in acute ischemic stroke trials, including a modified Treatment In Cerebral Ischemia (mTICI) score. ; (3) a standardized process to assess whether ischemic core and penumbral imaging methods meet the requirements to be considered as an acceptable selection tool in acute ischemic stroke trials. ; (4) the characteristics of a clinical and imaging data repository to facilitate the development and testing process described in recommendation no. 3. ; (5) the optimal study design for a clinical trial to evaluate whether advanced imaging adds value in selecting acute ischemic stroke patients for revascularization therapy. ; (6) the structure of a stroke neuroimaging network to implement and coordinate the recommendations listed above. All of these recommendations pertain to research, not to clinical care

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press