27 research outputs found
Applicability of current staging/categorization of α-synuclein pathology and their clinical relevance
In Parkinson’s disease (PD) and dementia with Lewy bodies (DLB) α-synuclein (αS) pathology is seen that displays a predictable topographic distribution. There are two staging/categorization systems, i.e. Braak’s and McKeith’s, currently in use for the assessment of αS pathology. The aim of these diagnostic strategies in pathology is, in addition to assess the stage/severity of pathology, to assess the probabilities of the related clinical symptomatology i.e. dementia and extrapyramidal symptoms (EPS). Herein, we assessed the applicability of these two staging/categorization systems and the frequency of dementia and EPS in a cohort of 226 αS-positive-subjects. These subject were selected from a large autopsy sample (n = 1,720), irrespective of the clinical presentation, based on the detection of αS-immunoreactivity (IR) in one of the most vulnerable nuclei; in the dorsal motor nucleus of vagus, substantia nigra and basal forebrain. The frequency of αS-IR lesions in this large cohort was 14% (248 out of 1,720). If applicable, each of the 226 subjects with all required material available was assigned a neuropathological stage/category of PD/DLB and finally the neuropathological data was analyzed in relation to dementia and EPS. 83% of subjects showed a distribution pattern of αS-IR that was compatible with the current staging/categorization systems. Around 55% of subjects with widespread αS pathology (Braak’s PD stages 5–6) lacked clinical signs of dementia or EPS. Similarly, in respect to those subjects that fulfilled the McKeith criteria for diffuse neocortical category and displaying only mild concomitant Alzheimer’s disease-related pathology, only 48% were demented and 54% displayed EPS. It is noteworthy that some subjects (17%) deviated from the suggested caudo-rostral propagation suggesting alternative routes of progression, perhaps due to concomitant diseases and genetic predisposition. In conclusion, our results do indeed confirm that current staging/categorization systems can readily be applied to most of the subjects with αS pathology. However, finding that around half of the subjects with abundant αS pathology remain neurologically intact is intriguing and raises the question whether we do assess the actual disease process
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 research