Animal models of amyotrophic lateral sclerosis: A comparison of model validity

Animal models are necessary to investigate the pathogenic features underlying motor neuron degeneration and for therapeutic development in amyotrophic lateral sclerosis (ALS). Measures of model validity allow for a critical interpretation of results from each model and caution from over-interpretation of experimental models. Face and construct validity refer to the similarity in phenotype and the proposed causal factor to the human disease, respectively. More recently developed models are restricted by limited phenotype characterization, yet new models hold promise for novel disease insights, thus highlighting their importance. In this article, we evaluate the features of face and construct validity of our new zebrafish model of environmentally-induced motor neuron degeneration and discuss this in the context of current environmental and genetic ALS models, including C9orf72, mutant Cu/Zn superoxide dismutase 1 and TAR DNA-binding protein 43 mouse and zebrafish models. In this mini-review, we discuss the pros and cons to validity criteria in each model. Our zebrafish model of environmentally-induced motor neuron degeneration displays convincing features of face validity with many hallmarks of ALS-like features, and weakness in construct validity. However, the value of this model may lie in its potential to be more representative of the pathogenic features underlying sporadic ALS cases, where environmental factors may be more likely to be involved in disease etiology than single dominant gene mutations. It may be necessary to compare findings between different strains and species modeling specific genes or environmental factors to confirm findings from ALS animal models and tease out arbitrary strain- and overexpression-specific effects

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.Peer reviewe

Erratum: Corrigendum: Sequence and comparative analysis of the chicken genome provide unique perspectives on vertebrate evolution

International Chicken Genome Sequencing Consortium. The Original Article was published on 09 December 2004. Nature432, 695–716 (2004). In Table 5 of this Article, the last four values listed in the ‘Copy number’ column were incorrect. These should be: LTR elements, 30,000; DNA transposons, 20,000; simple repeats, 140,000; and satellites, 4,000. These errors do not affect any of the conclusions in our paper. Additional information. The online version of the original article can be found at 10.1038/nature0315

Sequence and comparative analysis of the chicken genome provide unique perspectives on vertebrate evolution

We present here a draft genome sequence of the red jungle fowl, Gallus gallus. Because the chicken is a modern descendant of the dinosaurs and the first non-mammalian amniote to have its genome sequenced, the draft sequence of its genome--composed of approximately one billion base pairs of sequence and an estimated 20,000-23,000 genes--provides a new perspective on vertebrate genome evolution, while also improving the annotation of mammalian genomes. For example, the evolutionary distance between chicken and human provides high specificity in detecting functional elements, both non-coding and coding. Notably, many conserved non-coding sequences are far from genes and cannot be assigned to defined functional classes. In coding regions the evolutionary dynamics of protein domains and orthologous groups illustrate processes that distinguish the lineages leading to birds and mammals. The distinctive properties of avian microchromosomes, together with the inferred patterns of conserved synteny, provide additional insights into vertebrate chromosome architecture

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