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

Genetic associations at 53 loci highlight cell types and biological pathways relevant for kidney function.

Reduced glomerular filtration rate defines chronic kidney disease and is associated with cardiovascular and all-cause mortality. We conducted a meta-analysis of genome-wide association studies for estimated glomerular filtration rate (eGFR), combining data across 133,413 individuals with replication in up to 42,166 individuals. We identify 24 new and confirm 29 previously identified loci. Of these 53 loci, 19 associate with eGFR among individuals with diabetes. Using bioinformatics, we show that identified genes at eGFR loci are enriched for expression in kidney tissues and in pathways relevant for kidney development and transmembrane transporter activity, kidney structure, and regulation of glucose metabolism. Chromatin state mapping and DNase I hypersensitivity analyses across adult tissues demonstrate preferential mapping of associated variants to regulatory regions in kidney but not extra-renal tissues. These findings suggest that genetic determinants of eGFR are mediated largely through direct effects within the kidney and highlight important cell types and biological pathways

The PECAn image and statistical analysis pipeline identifies Minute cell competition genes and features.

Acknowledgements: We wish to thank Rafael Carazo-Salas and his laboratory for their guidance in designing, building, and validating the image analysis pipeline. We also thank Stephen Cross and Anatole Chessel for their help in evaluating the software and Daniel Lawson and Susan Connolly for assisting us in implementing, interpreting, and understanding statistical packages in R. Thanks to Cristina Villa del Campo and Miguel Torres for sharing sample images of a postnatal mouse heart. Finally, we thank the Wolfson Bioimaging Facility for access to microscopes. This work was supported by a Cancer Research UK Programme Foundation Award to E.P. (Grant C38607/A26831) and Wellcome Trust Senior Research Fellowships to E.P. (205010/Z/, 16/Z and 224675/Z/21/Z). J.L. is supported by an EMBO Postdoctoral Fellowship (EMBO ALTF 947-2021).Investigating organ biology often requires methodologies to induce genetically distinct clones within a living tissue. However, the 3D nature of clones makes sample image analysis challenging and slow, limiting the amount of information that can be extracted manually. Here we develop PECAn, a pipeline for image processing and statistical data analysis of complex multi-genotype 3D images. PECAn includes data handling, machine-learning-enabled segmentation, multivariant statistical analysis, and graph generation. This enables researchers to perform rigorous analyses rapidly and at scale, without requiring programming skills. We demonstrate the power of this pipeline by applying it to the study of Minute cell competition. We find an unappreciated sexual dimorphism in Minute cell growth in competing wing discs and identify, by statistical regression analysis, tissue parameters that model and correlate with competitive death. Furthermore, using PECAn, we identify several genes with a role in cell competition by conducting an RNAi-based screen

Identification of sequence variants influencing immunoglobulin levels.

To access publisher's full text version of this article click on the hyperlink belowImmunoglobulins are the effector molecules of the adaptive humoral immune system. In a genome-wide association study of 19,219 individuals, we found 38 new variants and replicated 5 known variants associating with IgA, IgG or IgM levels or with composite immunoglobulin traits, accounted for by 32 loci. Variants at these loci also affect the risk of autoimmune diseases and blood malignancies and influence blood cell development. Notable associations include a rare variant at RUNX3 decreasing IgA levels by shifting isoform proportions (rs188468174[C>T]: P = 8.3 × 10(-55), β = -0.90 s.d.), a rare in-frame deletion in FCGR2B abolishing IgG binding to the encoded receptor (p.Asn106del: P = 4.2 × 10(-8), β = 1.03 s.d.), four IGH locus variants influencing class switching, and ten new associations with the HLA region. Our results provide new insight into the regulation of humoral immunity.Swedish Foundation for Strategic Research Marianne and Marcus Wallenberg Foundation Knut and Alice Wallenberg Foundation Swedish Research Counci